Category Archives: Education

The Performance Management in Higher Education

This is an excerpt from my latest academic article, entitled; “Using the balanced scorecard as a performance management tool in higher education” that will be published in Sage’s “Management in Education” (Journal).


The higher education institutions (HEIs) are competing in a global marketplace, particularly those which are operating in the contexts of neoliberal policymaking (Fadeeva and Mochizuki, 2010; Deem et al., 2008; Olssen and Peters, 2005; Bleiklie, 2001). Several universities are characterized by their de-centralized leadership as they operate with budget constraints (Smeenk, Teelken, Eisinga and Doorewaard, 2008; Bleiklie, 2001). Notwithstanding, their stakeholders expect their increased accountability and quality assurance, in terms of their efficiency, economy and effectiveness (Witte and López-Torres, 2017; Smeek et al., 2008). Hence, HEIs set norms, standards, benchmarks, and quality controls to measure their performance; as they are increasingly market-led and customer-driven (Jauhiainen, Jauhiainen, Laiho and Lehto, 2015; Billing, 2004; Etzkowitz, et al., 2000). Specifically, the universities’ performance is having a positive effect on the economic development of societies; through the provision of inclusive, democratized access to quality education and high impact research (Arnesen & Lundahl, 2006). Moreover, the educational institutions are also expected to forge strong relationships with marketplace stakeholders, including business and industry (Waring, 2013).

As a result, many universities have adapted, or are trying to adapt to the changing environment as they re-structure their organization and put more emphasis on improving their organizational performance. These developments have inevitably led to the emergence of bureaucratic procedures and processes (Jauhiainen et al., 2015).  HEIs have even started using the corporate language as they formulate plans, set objectives, and use performance management criteria to control their resources (Smeenk et al., 2008; Ball, 2003). For instance, the Finnish universities have introduced new steering mechanisms, including the performance systems in budgeting, organizational reforms, management methods and salary systems (Camilleri, 2018; Jauhiainen et al., 2015). Previously, Welch (2007) noted that HEIs were adopting new modes of governance, organizational forms, management styles, and values that were prevalent in the private business sector. The logic behind these new managerial reforms was to improve the HEIs’ value for money principles (Waring, 2013; Deem, 1998). Therefore, the financing of HEIs is a crucial element in an imperfectly competitive, quasi-market model (Marginson, 2013; Olssen and Peters, 2005; Enders, 2004; Dill, 1997).

Academic commentators frequently suggest that the managerial strategies, structures, and values that belong to the ‘private sector’ are leading to significant improvements in the HEIs’ performance (Waring, 2013; Teelken, 2012; Deem and Brehony, 2005; Deem, 1998). On the other hand, critics argue that the ‘managerial’ universities are focusing on human resource management (HRM) practices that affect the quality of their employees’ job performance (Smeenk et al., 2008). Very often, HEIs are employing bureaucratic procedures involving time-consuming activities that could otherwise have been invested in research activities and / or to enhance teaching programs. The HEIs’ management agenda is actually imposed on the academics’ norms of conduct and on their professional behaviors. Therefore, the universities’ leadership can affect the employees’ autonomies as they are expected to comply with their employers’ requirements (Deem and Brehony, 2005). Smeenk et al. (2008) posited that this contentious issue may lead to perennial conflicts between the employees’ values and their university leaders’ managerial values; resulting in lower organizational commitment and reduced productivities.

The HEIs’ managerial model has led to a shift in the balance of power from the academics to their leaders as the universities have developed quality assurance systems to monitor and control their academic employees’ performance (Camilleri, 2018; Cardoso, Tavares and Sin, 2015). This trend towards managerialism can be perceived as a lack of trust in the academic community. However, the rationale behind managerialism is to foster a performative culture among members of staff, as universities need to respond to increased competitive pressures for resources, competences and capabilities (Decramer et al., 2013; Marginson, 2006; 2001; Enders, 2004). These issues have changed the HEIs’ academic cultures and norms in an unprecedented way (Chou and Chan, 2016; Marginson, 2013).

HEIs have resorted to the utilization of measures and key performance indicators to improve their global visibility. Their intention is to raise their institutions’ profile by using metrics that measure productivity. Many universities have developed their own performance measures or followed frameworks that monitor the productivity of academic members of staff (Taylor and Baines, 2012). Very often, their objective is to audit their academic employees’ work. However, their work cannot always be quantified and measured in objective performance evaluations. For instance, Waring (2013) argued that academic employees are expected to comply with their employers’ performance appraisals (PAs) and their form-filling exercises. The rationale behind the use of PAs is to measure the employees’ productivity in the form of quantifiable performance criteria. Hence, the PA is deemed as a vital element for the evaluation of the employees’ performance (Kivistö et al., 2017; Dilts et al., 1994). The PA can be used as part of a holistic performance management approach that measures the academics’ teaching, research and outreach. This performance management tool can possibly determine the employees’ retention, promotion, tenure as well as salary increments (Subbaye, 2018; Ramsden, 1991).

Therefore, PAs ought to be clear and fair. Their administration should involve consistent, rational procedures that make use of appropriate standards. The management’s evaluation of the employees’ performance should be based on tangible evidence. In a similar vein, the employees need to be informed of what is expected from them (Dilts et al., 1994). They should also be knowledgeable about due processes for appeal arising from adverse evaluations, as well as on grievance procedures, if any (Author, 2018). In recent years; the value of the annual performance appraisals (PAs) has increasingly been challenged in favor of more regular ‘performance conversations’ (Aguinis, 2013; Herdlein, Kukemelk and Türk, 2008). Therefore, regular performance feedback or the frequent appraisal of employees still remain a crucial aspect of the performance management cycle. Pace (2015) reported that the PA was used to develop the employees’ skills, rather than for administrative decisions. In a similar vein, the University of Texas (2019) HR page suggests that the appraisers’ role is “to set expectations, gather data, and provide ongoing feedback to employees, to assist them in utilizing their skills, expertise and ideas in a way that produces results”. However, a thorough literature review suggests that there are diverging views among academia and practitioners on the role of the annual PA, the form it should take, and on its effectiveness in the realms of higher education (Herdlein et al., 2008; DeNisi and Pritchard, 2006).

The Performance Management Frameworks

The HEIs’ evaluative systems may include an analysis of the respective universities’ stated intentions, peer opinions, government norms and comparisons, primary procedures from ‘self-evaluation’ through external peer review. These metrics can be drawn from published indicators and ratings, among other frameworks (Billing, 2004).  Their performance evaluations can be either internally or externally driven (Cappiello and Pedrini, 2017). The internally driven appraisal systems put more emphasis on self-evaluation and self-regulatory activities (Baxter, 2017; Bednall, Sanders and Runhaar, 2014; Dilts et al., 1994). Alternatively, the externally driven evaluative frameworks may involve appraisal interviews that assess the quality of the employees’ performance in relation to pre-established criteria (DeNisi and Pritchard, 2006; Cederblom, 1982).

Many countries, including the European Union (EU) states have passed relevant legislation, regulatory standards and guidelines for the HEIs’ quality assurance (Baxter, 2017), and for the performance evaluations of their members of staff (Kohoutek et al., 2018; Cardoso et al., 2015; Bleiklie, 2001). Of course, the academic employees’ performance is usually evaluated against their employers’ priorities, commitments, and aims; by using relevant international benchmarks and targets (Lo, 2009). The academics are usually appraised on their research impact, teaching activities and outreach (QS Ranking, 2019; THE, 2019). Their academic services, including their teaching resources, administrative support, and research output all serve as performance indicators that can contribute to the reputation and standing of the HEI that employs them (Geuna and Martin, 2003).

Notwithstanding, several universities have restructured their faculties and departments to enhance their research capabilities. Their intention is to improve their institutional performance in global rankings (Lo, 2014). Therefore, HEIs recruit academics who are prolific authors that publish high-impact research with numerous citations in peer reviewed journals (Wood and Salt, 2018; Author, 2018). They may prefer researchers with scientific or quantitative backgrounds, regardless of their teaching experience (Chou and Chan, 2016). These universities are prioritizing research and promoting their academics’ publications to the detriment of university teaching. Thus, the academics’ contributions in key international journals is the predominant criterion that is used to judge the quality of academia (Billing, 2004). For this reason, the vast majority of scholars are using the English language as a vehicle to publish their research in reputable, high impact journals (Chou and Chan, 2016). Hence, the quantity and quality of their research ought to be evaluated through a number of criteria (Lo, 2014; 2011; Dill and Soo, 2005).

University ranking sites, including (THE) and the QS Rankings, among others, use performance indicators to classify and measure the quality and status of HEIs. This would involve the gathering and analysis of survey data from academic stakeholders. THE and QS, among others clearly define the measures, their relative weight, and the processes by which the quantitative data is collected (Dill and Soo, 2005). The Academic Ranking of World Universities (ARWU) relies on publication-focused indicators as 60 percent of its weighting is assigned to the respective university’s research output. Therefore, these university ranking exercises are surely affecting the policies, cultures and behaviors of HEIs and of their academics (Wood and Salt, 2018; De Cramer et al., 2013; Lo, 2013).  For instance, the performance indicators directly encourage the recruitment of international faculty and students. Other examples of quantitative metrics include the students’ enrolment ratios, graduate rates, student drop-out rates, the students’ continuation of studies at the next academic level, and the employability index of graduates, among others. Moreover, qualitative indicators can also provide insightful data on the students’ opinions and perceptions about their learning environment. The HEIs could evaluate the students’ satisfaction with teaching; satisfaction with research opportunities and training; perceptions of international and public engagement opportunities; ease of taking courses across boundaries, and may also determine whether there are administrative / bureaucratic barriers for them (Kivistö et al., 2017; Jauhiainen et al., 2015; Ramsden, 1991). Hence, HEIs ought to continuously re-examine their strategic priorities and initiatives. It is in their interest to regularly analyze their performance management frameworks through financial and non-financial indicators, in order to assess the productivity of their human resources. Therefore, they should regularly review educational programs and course curricula (Kohoutek et al., 2018; Brewer and Brewer, 2010). On a faculty level, the university leaders ought to keep a track record of changes in the size of departments; age and distribution of academic employees; diversity of students and staff, in terms of gender, race and ethnicity, et cetera. In addition, faculties could examine discipline-specific rankings; and determine the expenditures per academic member of staff, among other options (Author, 2018).

The balanced scorecard

The balanced scorecard (BSC) was first introduced by Kaplan and Norton (1992) in their highly cited article, entitled “The Balanced Scorecard: Measures that Drive Performance”. BSC is an integrated results-oriented, performance management tool, consisting of financial and non-financial measures that link the organizations’ mission, core values, and vision for the future with strategies, targets, and initiatives that are designed to bring continuous improvements (Taylor and Baines, 2012; Wu, Lin and Chang, 2011; Beard, 2009; Umashankar and Dutta, 2007; Cullen, Joyce, Hassall and Broadbent, 2003; Kaplan and Norton, 1992). Its four performance indicators play an important role in translating strategy into action; and can be utilized to evaluate the performance of HEIs. BSC provides a balanced performance management system as it comprises a set of performance indices that can assess different organizational perspectives (Taylor and Baines, 2012). For BSC, the financial perspective is a core performance measure. However, the other three perspectives namely: customer (or stakeholder), organizational capacity and internal process ought to be considered in the performance evaluations of HEIs, as reported in the following table:

BSC Higher Education

The balanced scorecard approach in higher education

Cullen et al. (2003) suggested that the UK’s Higher Education Funding Council for England (HEFCE), the Scottish Funding Council (SHEFC), the Higher Education Funding Council for Wales (HEFCW), as well as the Department for Employment and Learning (DELNI) have incorporated the BSC’s targets in their Research Excellence Framework. Furthermore, other HEI targets, including: the students’ completion rates, the research impact of universities, collaborative partnerships with business and industry, among others, are key metrics that are increasingly being used in international benchmarking exercises, like the European Quality Improvement System (EQUIS), among others. Moreover, BSC can be used to measure the academic employees’ commitment towards their employer (Umashankar and Dutta, 2007; McKenzie, and Schweitzer, 2001). Notwithstanding, Wu, Lin and Chang (2011) contended that the BSC’s ‘‘organizational capacity’’ is related to the employee development, innovation and learning. Hence the measurement of the HEIs’ intangible assets, including their intellectual capital is affected by other perspectives, including the financial one (Taylor and Baines, 2012). This table summarizes some of the strengths and weaknesses of the balanced scorecard.

BSC

BSC is widely used to appraise the financial and non-financial performance of businesses and public service organizations including HEIs. Many HEI leaders are increasingly following business-like approaches as they are expected to operate in a quasi-market environment (Marginson, 2013). They need to scan their macro environment to be knowledgeable about the opportunities and threats from the political, economic, social and technological factors. Moreover, they have to regularly analyze their microenvironment by evaluating their strengths and weaknesses.  Hence, several HEIs are increasingly appraising their employees as they assess their performance on a regular basis. They may even decide to take remedial actions when necessary.  Therefore, BSC can also be employed by HEIs to improve their academic employees’ productivity levels (Marginson, 2013; 2000).


A pre-publication version of the full article is available through ResearchGate and Academia.edu.

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Filed under academia, Balanced Scorecard, Education, Education Leadership, Higher Education, Human Resources, human resources management, performance appraisals, performance management, University Ranking, webometrics

The Students’ Engagement with Mobile Learning Technologies

These are excerpts from our latest academic article.

How to Cite: Camilleri, M.A. & Camilleri, A.C. (2019). The Students’ Readiness to Engage with Mobile Learning Apps. Interactive Technology and Smart Education. https://www.emerald.com/insight/content/doi/10.1108/ITSE-06-2019-0027/full/html


Hand-held mobile devices such as smart phones and tablets allow individuals, including students, to access and review online (educational) content from virtually anywhere. The mobile applications (apps) can provide instant access to the schools’ learning resources (Camilleri & Camilleri, 2019b; Sánchez & Isaías, 2017; Cheon, Lee, Crooks & Song, 2012). Therefore, they are increasingly being utilized in the context of primary education to improve the student experience. Relevant theoretical underpinnings reported that more primary level students are utilizing mobile learning technologies to engage with their instructors (Rodríguez, Riaza & Gómez, 2017; Sánchez & Isaías, 2018). Notwithstanding, it is much easier for the younger pupils to mobile apps to read eBooks, as hard-copy textbooks need to be carried in their bags. Arguably, the proliferation of portable technologies like tablets are lighter and less bulky than laptop computers. Hence, primary school students can easily use mobile technologies anywhere, beyond the traditional classroom environment (Rodríguez et al., 2017). Currently, there is a wide variety of educational apps that are readily available on a wide array of mobile devices (Chee, Yahaya, Ibrahim &Hasan, 2017; Domingo & Garganté, 2016). Such interactive technologies can improve the delivery of quality education as teachers provide direct feedback to their students, in real time. Some of the mobile apps can even engage primary school students in immersive learning experiences (Camilleri & Camilleri,2019c; Isaias, Reis, Coutinho & Lencastre, 2017).

On the other hand, other academic literature posited that some students may not want to engage in mobile learning. Very often, commentators implied that the mobile technologies have their own limitations (Cheon et al., 2012; Wang, Wu & Wang, 2009). A few practitioners contended that mobile devices had small screens with low resolutions. Alternatively, some argued about their slow connection speeds, or pointed out that they lacked standardization features  (Sánchez & Isaías, 2017; Camilleri & Camilleri,2017).

As a matter of fact, Android, Apple and Microsoft Windows have different operating systems. As a result, learning apps may have to be customized to be compatible with such systems. Moreover, individuals, including primary school students may hold different attitudes towards the use of mobile devices. There may be students who may be motivated to engage with mobile technologies (Sánchez & Isaias, 2018; Ciampa, 2014) as they use these devices to play games, watch videos, or to chat with their friends, online (Wang et al., 2009). In this case, the primary school students may use their mobile devices for hedonic reasons, rather than to engage in mobile learning activities. Such usage of the mobile technologies can possibly result in undesired educational outcomes. Nevertheless, those primary level students who already own or have instant access to a mobile device may easily become habitual users of this technology; as they use it for different purposes. However, there is still limited research in academia that explores these students’ readiness to engage in mobile learning at home, and at school.


Results

The findings in this study are consistent with the argument that digital natives are increasingly immersing themselves in digital technologies (Bourgonjon et al., 2010), including educational games (Camilleri & Camilleri,2019; Ge & Ifenthaler, 2018; Carvalho et al., 2015, Wouters et al., 2013). However, the results have shown that there was no significant relationship between the perceived ease of the gameplay and the children’s enjoyment in them. Furthermore, the stepwise regression analysis revealed that there was no significant relationship between the normative expectations and the children’s engagement with the educational apps; although it was evident (from the descriptive statistics) that the parents were encouraging their children to play the games at home and at school. This research relied on previously tried and tested measures that were drawn from the educational technology literature in order to explore the hypothesized relationships. There is a common tendency in academic literature to treat the validity and reliability of quantitative measures from highly cited empirical papers as given.

Future studies may use different sampling frames, research designs and methodologies to explore this topic. To the best of our knowledge, there is no other empirical study that has validated the technology acceptance model within a primary school setting. Further work is needed to replicate the findings of this research in a similar context.


References (the full bibliography of this paper)

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Bourgonjon, J., Valcke, M., Soetaert, R., and Schellens, T. (2010), “Students’ perceptions about the use of educational games in the classroom”, Computers & Education, Vol. 54, No. 4, pp. 1145-1156.

Burguillo, J.C. (2010), “Using game theory and competition-based learning to stimulate student motivation and performance”, Computers & Education, Vol. 55, No. 2, pp. 566-575.

Camilleri, M.A. and Camilleri, A. (2017a), “The Technology Acceptance of Mobile Applications in Education”, In Sánchez, I.A. & Isaias, P. (Eds) 13th International Conference on Mobile Learning (Budapest, 11th April). Proceedings, pp 41-48. International Association for Development of the Information Society.

Camilleri, M.A., and Camilleri, A.C. (2017b), “Digital learning resources and ubiquitous technologies in education”, Technology, Knowledge and Learning, Vol. 22, No. 1, pp. 65-82.

Camilleri, M. A., and  Camilleri, A. (2019a), “Student Centred Learning Through Serious Games”, 13th Annual International Technology, Education and Development Conference. Valencia, Spain (March, 2019). International Academy of Technology, Education and Development (IATED).

Camilleri, A.C., and Camilleri, M.A. (2019b), “Mobile Learning via Educational Apps: An Interpretative Study”. In Shun-Wing N.G., Fun, T.S. & Shi, Y. (Eds.) 5th International Conference on Education and Training Technologies (ICETT 2019). Seoul, South Korea (May, 2019). International Economics Development and Research Center (IEDRC).

Camilleri, A.C., and Camilleri, M.A. (2019c), “The Students Intrinsic and Extrinsic Motivations to Engage with Digital Learning Games”, In Shun-Wing N.G., Fun, T.S. & Shi, Y. (Eds.) 5th International Conference on Education and Training Technologies (ICETT 2019). Seoul, South Korea (May, 2019). International Economics Development and Research Center (IEDRC).

Carvalho, M.B., Bellotti, F., Berta, R., De Gloria, A., Sedano, C.I., Hauge, H.B., Hu, J., and Rauterberg, M. (2015), “An activity theory-based model for serious games analysis and conceptual design”, Computers & Education, Vol. 87, pp.166-181.

Chang, C.T., Hajiyev, J., and Su, C.R. (2017), “Examining the students’ behavioral intention to use e-learning in Azerbaijan? The general extended technology acceptance model for e-learning approach”, Computers & Education, Vol. 111, pp. 128-143.

Chee, K. N., Yahaya, N., Ibrahim, N. H., and Hasan, M. N. (2017). Review of mobile learning trends 2010-2015: A meta-analysis. Journal of Educational Technology & Society20(2), 113-126.

Chen, K. C. and Jang, S. J. (2010), “Motivation in online learning: Testing a model of self-determination theory”, Computers in Human Behavior, Vol. 26, No. 4, pp. 741-752.

Cheon, J., Lee, S., Crooks, S. M. and Song, J. (2012), “An investigation of mobile learning readiness in higher education based on the theory of planned behavior”, Computers & Education, Vol. 59, No. 3, pp. 1054-1064.

Ciampa, K. (2014), “Learning in a mobile age: an investigation of student motivation”, Journal of Computer Assisted Learning, Vol. 30, No. 1, pp. 82-96.

Connolly, T.M., Boyle, E.A., MacArthur, E.  Hainey, T., and Boyle, J.M. (2012), “A systematic literature review of empirical evidence on computer games and serious games”, Computers & Education, Vol. 59, No. 2, pp. 661-686.

Davis, F.D. (1989), “Perceived usefulness, perceived ease of use, and user acceptance of information technology”, MIS Quarterly, Vol. 13, No. 3, pp. 319-340.

Davis, F.D., Bagozzi, R.P., and Warshaw, P.R. (1989), “User acceptance of computer technology: a comparison of two theoretical models”, Management Science, Vol. 35, No. 8, pp. 982-1003.

Dickey, M.D. (2011), “Murder on Grimm Isle: The impact of game narrative design in an educational game‐based learning environment”, British Journal of Education Technology, Vol. 42, No.  3, pp. 456-469.

Domingo, M. G. and Garganté, A. B. (2016). Exploring the use of educational technology in primary education: Teachers’ perception of mobile technology learning impacts and applications’ use in the classroom. Computers in Human Behavior, Vol. 56, pp. 21-28.

Dunne, Á., Lawlor, M. A., and Rowley, J. (2010), “Young people’s use of online social networking sites–a uses and gratifications perspective”, Journal of Research in International Marketing,. Vol. 4, No. 1, pp.  46-58.

Ge, X., and Ifenthaler, D. (2018), “Designing engaging educational games and assessing engagement in game-based learning”, In Gamification in Education: Breakthroughs in Research and Practice, IGI Global, Hershey, USA, pp. 1-19.

Harris, J. Mishra, P., and Koehler, M. (2009), “Teachers’ technological pedagogical content knowledge and learning activity types: Curriculum-based technology integration reframed”, Journal of Research on Technology in Education, Vol. 41, No. 4, pp. 393-416.

Huang, W.H., Huang, W.Y., and Tschopp, J. (2010), “Sustaining iterative game playing processes in DGBL: The relationship between motivational processing and outcome processing”,  Computers & Education, Vol. 55, No. 2, pp. 789-97.

Hwang, G.J., and Wu, P.H.  (2012), “Advancements and trends in digital game‐based learning research: a review of publications in selected journals from 2001 to 2010”, British. Journal of Education Technology, Vol. 43, No. 1, pp. E6-E10.

Isaias, P., Reis, F., Coutinho, C. and Lencastre, J. A. (2017), “Empathic technologies for distance/mobile learning: An empirical research based on the unified theory of acceptance and use of technology (UTAUT)”, Interactive Technology and Smart Education, Vol. 14, No. 2, pp. 159-180.

Lee, M. K., Cheung, C. M., and Chen, Z. (2005), “Acceptance of Internet-based learning medium: the role of extrinsic and intrinsic motivation”, Information & Management,. Vol. 42, No. 8, pp. 1095-1104.

Li, H., Liu, Y., Xu, X., Heikkilä, J., and Van Der Heijden, H. (2015), “Modeling hedonic is continuance through the uses and gratifications theory: An empirical study in online games”, Computers in Human Behavior, Vol. 48, pp. 261-272.

Park, S.Y. (2009), “An analysis of the technology acceptance model in understanding university students’ behavioral intention to use e-learning”, Education. Technology & Society, Vol. 12, No. 3, pp. 150-162.

Park, S. Y., Nam, M. W., and Cha, S. B. (2012), “University students’ behavioral intention to use mobile learning: Evaluating the technology acceptance model”, British Journal of Education Technology, Vol. 43, No. 4, pp. 592-605.

Rodríguez, A. I., Riaza, B. G., & Gómez, M. C. S. (2017), “Collaborative learning and mobile devices: An educational experience in Primary Education”, Computers in Human Behavior, Vol. 72, pp. 664-677.

Ryan, R. M., and Deci, E. L. (2000), “Intrinsic and extrinsic motivations: Classic definitions and new directions”, Contemporary Education Psychology, Vol. 25, No. 1, pp. 54-67.

Sánchez, I. A., & Isaías, P. (2017), “Proceedings of the International Association for Development of the Information Society (IADIS)”, International Conference on Mobile Learning (13th, Budapest, Hungary, April 10-12, 2017). International Association for Development of the Information Society.

Sánchez, I. A., & Isaias, P. (2018), “Proceedings of the International Association for Development of the Information Society (IADIS)”, International Conference on Mobile Learning (14th, Lisbon, Portugal, April 14-16, 2018). International Association for Development of the Information Society.

Teo, T., Beng Lee, C., Sing Chai, C., and Wong, S.L. (2009), “Assessing the intention to use technology among pre-service teachers in Singapore and Malaysia: A multigroup invariance analysis of the Technology Acceptance Model (TAM)”, Computers & Education, Vol. 53, No. 3, pp. 1000-1009.

Venkatesh, V., Morris, M.G., Davis, G.B. and Davis, F.D. (2003), “User acceptance of information technology: Toward a unified view”, MIS Quarterly, Vol. 27, No. 3, pp. 425-478.

Venkatesh, V., Thong, Y.T.L., and Xu, X. (2012), “Consumer acceptance and use of information technology: extending the unified theory of acceptance and use of technology”, MIS Quarterly, Vol. 36, No.1, pp. 157-178.

Wang, Y. S., Wu, M. C., & Wang, H. Y. (2009), “Investigating the determinants and age and gender differences in the acceptance of mobile learning”, British Journal of Educational technology, Vol. 40, No. 1, pp. 92-118.

Wouters, P., Van Nimwegen, C., Van Oostendorp, H., and Van Der Spek, E.D. (2013), “A meta-analysis of the cognitive and motivational effects of serious games”,  Journal of Education Psychology,  Vol. 105, No.  2, pp. 249-266.


Related Publications

Camilleri, M.A. & Camilleri, A.C. (2019). The Acceptance and Use of Mobile Learning Applications in Higher Education. In Pfennig, A. & Chen, K.C. (Eds.) 3rd International Conference on Education and eLearning (ICEEL2019), Barcelona, Spain.

Camilleri, A.C. & Camilleri, M.A. (2019). The Students’ Perceived Use, Ease of Use and Enjoyment of Educational Games at Home and at School. 13th Annual International Technology, Education and Development Conference. Valencia, Spain (March, 2019). International Academy of Technology, Education and Development (IATED).Download this paper

Camilleri, M.A. & Camilleri, A. (2017). The Students’ Perceptions of Digital Game-Based Learning. In Pivec, M. & Grundler, J. (Ed.) 11th European Conference on Games Based Learning  (October). Proceedings, pp. 52-62, H JOANNEUM University of Applied Science, Graz, Austria, pp 56-62. http://toc.proceedings.com/36738webtoc.pdf Download this paper

Camilleri, M.A. & Camilleri, A. (2017). Measuring The Educators’ Behavioural Intention, Perceived Use And Ease Of Use Of Mobile Technologies. In Wood, G. (Ed) Re-connecting management research with the disciplines: Shaping the research agenda for the social sciences (University of Warwick, September). Proceedings, pp., British Academy of Management, UK. http://conference.bam.ac.uk/BAM2017/htdocs/conference_papers.php?track_name=%20Knowledge%20and%20Learning Download this paper

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Filed under Education, education technology, internet technologies, internet technologies and society, Marketing, Mobile, mobile learning

The Students Intrinsic and Extrinsic Motivations to Engage with Digital Learning Games

An Excerpt from one of my latest papers, entitled; “The Students’ Intrinsic and Extrinsic Motivations to Engage with Digital Learning Games”.

How to Cite: Camilleri, A.C. & Camilleri, M.A. (2019). The Students Intrinsic and Extrinsic Motivations to Engage with Digital Learning Games. In Shun-Wing N.G., Fun, T.S. & Shi, Y. (Eds.) 5th International Conference on Education and Training Technologies (ICETT 2019). Seoul, South Korea (May, 2019).


This contribution has explored the primary school’s grade three  students’ intrinsic and extrinsic motivations toward the use of educational games. It relied on the technology acceptance model to investigate the students’ perceived usefulness and ease of use of the  schools’ games ([7], [8], [15]). Moreover, the researchers have also  included the measuring items that explored the students’ perceived  enjoyment ([12], [13], [20]) as they investigated whether they  experienced normative pressures to play the educational games ([14], [22], [23]). The findings from the Wilcoxon test reported that the students played the school games at home, more than they did at school. They indicated that the school’s games were easy to play.

This study reported that the students recognized that the school’s games were useful and relevant as they were learning from them. Moreover, they indicated that the school’s educational games held their attention since they found them enjoyable and fun. The vast majority of the children played the educational games, both at home and at school. The findings in this study are consistent with the argument that digital natives are increasingly immersing
themselves in digital technologies ([2]), including educational games ([1], [4], [10], [11], [28]). However, the results have shown that there was no significant relationship between the perceived ease of the gameplay and the children’s enjoyment in them.

Furthermore, the stepwise regression analysis revealed that there was no significant relationship between the normative expectations and the children’s engagement with the educational games; although it was evident (from the descriptive statistics) that the parents were encouraging their children to play the games at home and at school.

This research relied on previously tried and tested measures that were drawn from the educational technology literature in order to explore the hypothesized relationships. There is common tendency  in academic literature to treat the validity and reliability of quantitative measures from highly cited empirical papers as given. In this case, the survey items in this study were designed and adapted for the primary school children who were in grade 3, in a
small European state. Future studies may use different sampling frames, research designs and methodologies to explore this topic. To the best of our knowledge, there is no other empirical study that has validated the technology acceptance model within a primary school setting. Further work is needed to replicate the findings of  this research in a similar context.

ACKNOWLEDGEMENTS
We thank the department of education, the school’s principal and her members of staff who have provided their invaluable support during the data gathering process.

REFERENCES
[1] Ge, X., and Ifenthaler, D. 2018. Designing engaging
educational games and assessing engagement in game-based
learning” In Gamification in Education: Breakthroughs in
Research and Practice, IGI Global, Hershey, USA, 1-19,

[2] Bourgonjon, J., Valcke, M., Soetaert, R., and Schellens, T.
2010, Students’ perceptions about the use of educational
games in the classroom. Comp. & Educ. 54, 4, 1145-1156.

[3] Hwang, G.J., and Wu, P.H. 2012. Advancements and trends
in digital game‐based learning research: a review of
publications in selected journals from 2001 to 2010. Brit. J.
of Educ. Tech. 43, 1, E6-E10.

[4] Carvalho, M.B., Bellotti, F., Berta, R., De Gloria, A.,
Sedano, C.I., Hauge, H.B., Hu, J., and Rauterberg, M. 2015.
An activity theory-based model for serious games analysis
and conceptual design. Comp. & Educ. 87, 166-181.

[5] Connolly, T.M., Boyle, E.A., MacArthur, E. Hainey, T., and
Boyle, J.M. 2012. A systematic literature review of empirical
evidence on computer games and serious games. Comp. &
Educ. 59, 2, 661-686.

[6] Burguillo, J.C. 2010. Using game theory and competitionbased
learning to stimulate student motivation and
performance. Comp. & Educ. 55, 2, 566-575.

[7] Dickey, M.D. 2011. Murder on Grimm Isle: The impact of
game narrative design in an educational game‐based learning
environment. Brit. J. of Educ. Tech, 42, 3, 456-469.

[8] Huang, W.H., Huang, W.Y., and Tschopp, J. 2010.
Sustaining iterative game playing processes in DGBL: The
relationship between motivational processing and outcome
processing. Comp. & Educ. 55, 2, 789-97.

[9] Harris, J. Mishra, P., and Koehler, M. 2009. Teachers’
technological pedagogical content knowledge and learning
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reframed. J. of Res. on Tech. in Educ. 41, 4, 393-416.

[10] Wouters, P., Van Nimwegen, C., Van Oostendorp, H., and
Van Der Spek, E.D. 2013. A meta-analysis of the cognitive
and motivational effects of serious games. J. of Educ. Psych.
105, 2, 249-266.

[11] Camilleri, M.A., and Camilleri, A. 2017. The Students’
Perceptions of Digital Game-Based Learning, In Pivec, M.
and Grundler, J. 11th European Conference on Games Based
Learning Proceedings (London, UK, October 04-05, 2017),
University of Applied Sciences, Graz, Austria, 56-62.

[12] Davis, F.D. 1989. Perceived usefulness, perceived ease of
use, and user acceptance of information technology. MIS
Quart. 319-340.

[13] Davis, F.D., Bagozzi, R.P., and Warshaw, P.R. 1989. User
acceptance of computer technology: a comparison of two
theoretical models. Mgt. Science, 35, 8, 982-1003.

[14] Ajzen, I. 1991. The theory of planned behavior. Org. Behav.
and Human Dec. Proc. 50, 2, 179-211.

[15] Lee, M. K., Cheung, C. M., and Chen, Z. 2005. Acceptance
of Internet-based learning medium: the role of extrinsic and
intrinsic motivation. Inf. & Mgt. 42, 8, 1095-1104.

[16] Chen, K. C. and Jang, S. J. 2010. Motivation in online
learning: Testing a model of self-determination theory.
Comp. in Human Behav. 26, 4, 741-752.

[17] Dunne, Á., Lawlor, M. A., and Rowley, J. 2010. Young
people’s use of online social networking sites–a uses and
gratifications perspective. Journal of Res. in Int. Mktg. 4, 1,
46-58.

[18] Li, H., Liu, Y., Xu, X., Heikkilä, J., and Van Der Heijden, H.
2015. Modeling hedonic is continuance through the uses and
gratifications theory: An empirical study in online games.
Comp. in Human Behav. 48, 261-272.

[19] Teo, T., Beng Lee, C., Sing Chai, C., and Wong, S.L. 2009.
Assessing the intention to use technology among pre-service
teachers in Singapore and Malaysia: A multigroup invariance
analysis of the Technology Acceptance Model (TAM).
Comp. & Educ. 53, 3, 1000-1009.

[20] Camilleri, M.A., and Camilleri, A.C. 2017. Digital learning
resources and ubiquitous technologies in education, Tech.,
Knowl. and Learng. 22, 1, 65-82.

[21] Park, S.Y. 2009. An analysis of the technology acceptance
model in understanding university students’ behavioral
intention to use e-learning, Educ. Tech. & Soc. 12, 3, 150-
162.

[22] Venkatesh, V., Morris, M.G., Davis, G.B. and Davis, F.D.
2003. User acceptance of information technology: Toward a
unified view. MIS Quart. 425-478.

[23] Venkatesh, V., Thong, Y.T.L., and Xu, X. 2012.Consumer
acceptance and use of information technology: extending the
unified theory of acceptance and use of technology. MIS
Quart. 157-178.

[24] Ryan, R. M., and Deci, E. L. 2000. Intrinsic and extrinsic
motivations: Classic definitions and new directions.
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[25] Cheon, J., Lee, S., Crooks, S. M. and Song, J. 2012. An
investigation of mobile learning readiness in higher
education based on the theory of planned behavior. Comp. &
Educ. 59, 3, 1054-1064.

[26] Chang, C.T., Hajiyev, J., and Su, C.R. 2017. Examining the
students’ behavioral intention to use e-learning in
Azerbaijan? The general extended technology acceptance
model for e-learning approach. Comp. & Educ. 111, 128-
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[27] Park, S. Y., Nam, M. W., and Cha, S. B. 2012. University
students’ behavioral intention to use mobile learning:
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[28] Camilleri, M.A. and Camilleri, A.C. 2017. The Technology
Acceptance of Mobile Applications in Education. In
Sánchez, I.A. and Isaias, P. (Eds) 13th
International Conference on Mobile Learning (London, UK,
10-11 April 2018). International Association for
Development of the Information Society Budapest, Hungary,
41-48.

Presentation is available at: https://www.slideshare.net/markanthonycamilleri/the-students-intrinsic-and-extrinsic-motivations-148006875

 

 

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Filed under digital games, Digital Learning Resources, digital media, Education, internet technologies, internet technologies and society

The Students’ Perceived Use, Ease of Use and Enjoyment of Educational Games

This is an excerpt from one of my latest empirical papers.

How to Cite: Camilleri, A.C. & Camilleri, M.A. (2019). The Students’ Perceived Use, Ease of Use and Enjoyment of Educational Games at Home and at School. 13th Annual International Technology, Education and Development Conference. Valencia, Spain (10-13 March, 2019). International Academy of Technology, Education and Development (IATED). https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3339163


gamesThis contribution has explored the primary school’s grade three students’ attitudes toward educational games. It relied on the technology acceptance model to investigate the students’ perceived usefulness and ease of use of the schools’ games ([10], [12], [44]). Moreover, the researchers have also included the measuring items that explored the students’ perceived enjoyment ([19]) as they investigated whether they experienced normative pressures to play the educational games ([10], [14], [20]). The findings from the Wilcoxon test reported that the students played the school games at home, more than they did at school. They indicated that the school’s games were easy to play. This study reported that the students recognized that the school’s games were useful and relevant as they were learning from them. Moreover, they indicated that the school’s educational games held their attention since they found them enjoyable and fun.

The vast majority of the children played the educational games, both at home and at school. The findings in this study are consistent with the argument that digital natives are increasingly immersing themselves in digital technologies ([45]), including educational games ([1], [3]). However, the results have shown that there was no significant relationship between the perceived ease of the gameplay and the children’s enjoyment in them. Furthermore, the stepwise regression analysis revealed that there was no significant relationship between the normative expectations and the children’s engagement with the educational games; although it was evident (from the descriptive statistics) that the parents were encouraging their children to play the games at home and at school.

This research relied on previously tried and tested measures that were drawn from the educational technology literature in order to explore the hypothesized relationships. There is common tendency in academic literature to treat the validity and reliability of quantitative measures from highly cited empirical papers as given. In this case, the survey items in this study were designed and adapted for the primary school children who were in grade 3, in a small European state. Future studies may use different sampling frames, research designs and methodologies to explore this topic. To the best of our knowledge, there is no other empirical study that has validated the technology acceptance model within a primary school setting. Further work is needed to replicate the findings of this research in a similar context.

REFERENCES (this is a full list of references that appeared in the bibliography section of the paper)

 
[1] J. Bourgonjon, M. Valcke, R. Soetaert, and T. Schellens, “Students’ perceptions about the use of educational games in the classroom,” Computers & Education, vol. 54, no. 4, pp. 1145-1156, 2010.

[2] S. Bennett, K. Maton, and L. Kervin, “The ‘digital natives’ debate: A critical review of the evidence,” British Journal of Educational Technology, vol. 39, no. 5, pp. 775-786, 2008.

[3] M. Prensky, “Digital natives, digital immigrants part 1,” On the horizon, vol. 9, no. 5, pp. 1-6, 2001.

[4] W. Nadeem, D. Andreini, J. Salo, and T. Laukkanen, “Engaging consumers online through websites and social media: A gender study of Italian Generation Y clothing consumers.” International Journal of Information Management, vol. 35, no. 4, pp. 432- 442, 2015.

[5] H.J. So, H. Choi, W.Y. Lim, and Y. Xiong, “Little experience with ICT: Are they really the Net Generation student-teachers?”, Computers & Education, vol. 59, no. 4, pp. 1234- 1245, 2012.

[6] J.M. Twenge, “The evidence for generation me and against generation we.” Emerging Adulthood 1, no. 1, pp. 11-16, 2013.

[7] D. Oblinger, and J. Oblinger, “Is it age or IT: First steps toward understanding the net generation,” Educating the Net Generation, 2(1-2), 20, 2015.

[8] N. Howe, and W. Strauss, “Millennials go to college: Strategies for a new generation on campus,” American Association of Collegiate Registrars and Admissions Officers (AACRAO), 2003.

[9] K. Gregor, T. Judd, B. Dalgarno, and J. Waycott, “Beyond natives and immigrants: exploring types of net generation students,” Journal of Computer Assisted Learning, vol. 26, no. 5, pp.332-343, 2010.

[10] T. Teo, “Modelling technology acceptance in education: A study of pre-service teachers,” Computers & Education 52, no. 2 (2009): 302-312, 2009.

[11] M. Fishbein, and I. Ajzen, “Belief, attitude, intention and behavior: An introduction to theory and research,” 1975.

[12] F.D. Davis, “Perceived usefulness, perceived ease of use, and user acceptance of information technology,” MIS Quarterly, pp. 319-340, 1989.

[13] F.D. Davis, R.P. Bagozzi, and P.R. Warshaw, “User acceptance of computer technology: a comparison of two theoretical models,” Management Science, vol. 35, no. 8, pp. 982- 1003, 1989.

[14] I. Ajzen, “The theory of planned behavior,” Organizational Behavior and Human Decision Processes, vol. 50, no. 2, pp. 179-211, 1991.

[15] V. Venkatesh, M.G. Morris, G.B. Davis, and F.D. Davis, “User acceptance of information technology: Toward a unified view,” MIS Quarterly, pp. 425-478, 2003.

[16] V. Venkatesh, J.Y.L. Thong, and X. Xu, “Consumer acceptance and use of information technology: extending the unified theory of acceptance and use of technology,” MIS Quarterly, pp. 157-178, 2012.

[17] S.Y. Park. “An analysis of the technology acceptance model in understanding university students’ behavioral intention to use e-learning,” Educational Technology & Society, vol. 12, no. 3, pp. 150-162, 2009.

[18] P. Legris, J. Ingham, and P. Collerette, “Why do people use information technology? A critical review of the technology acceptance model,” Information & Management, vol. 40, no. 3, pp. 191-204, 2003.

[19] H. Nysveen, P.E. Pedersen, and H. Thorbjørnsen, “Intentions to use mobile services: Antecedents and cross-service comparisons,” Journal of the Academy of Marketing Science, vol. 33, no. 3, pp. 330-346, 2005.

[20] L.M. Maruping, B. Hillol, V. Venkatesh, and S.A. Brown, “Going beyond intention Integrating behavioral expectation into the unified theory of acceptance and use of technology,” Journal of the Association for Information Science and Technology, vol. 68, no. 3, pp. 623-637, 2017.

[21] V. Venkatesh, and M.G. Morris, “Why don’t men ever stop to ask for directions? Gender, social influence, and their role in technology acceptance and usage behavior.” MIS Quarterly, pp. 115-139, 2000.

[22] M.A. Camilleri and A. Camilleri, “The Students’ Perceptions of Digital Game-Based Learning,” In M. Pivec and J. Grundler, 11th European Conference on Games Based Learning (October). Proceedings, University of Applied Sciences, Graz, Austria, pp 56- 62, 2017.

[23] T. Teo, and M. Zhou, “Explaining the intention to use technology among university students: a structural equation modeling approach,” Journal of Computing in Higher Education, vol. 26, no. 2, pp. 124-142, 2014.

[24] T. Doleck, P. Bazelais, and D.J. Lemay, “Examining the antecedents of social networking sites use among CEGEP students,” Education and Information Technologies, vol. 22, no. 5, pp. 2103-2123, 2017.

[25] B. Wu, and X. Chen, “Continuance intention to use MOOCs: Integrating the technology acceptance model (TAM) and task technology fit (TTF) model,” Computers in Human Behavior, vol. 67, pp. 221-232, 2017.

[26] C.T. Chang, J. Hajiyev, and C.R. Su, “Examining the students’ behavioral intention to use e-learning in Azerbaijan? The general extended technology acceptance model for elearning approach,” Computers & Education, vol. 111, pp. 128-143, 2017.

[27] I. Arpaci, K. Kilicer, and S. Bardakci, “Effects of security and privacy concerns on educational use of cloud services,” Computers in Human Behavior, vol. 45, pp. 93-98,
2015.

[28] A.F. Agudo-Peregrina, Á. Hernández-García, and F.J. Pascual-Miguel, “Behavioral intention, use behavior and the acceptance of electronic learning systems: Differences between higher education and lifelong learning,” Computers in Human Behavior, vol. 34,
pp. 301-314, 2014.

[29] F. Paraskeva, H. Bouta, and A. Papagianni. “Individual characteristics and computer self-efficacy in secondary education teachers to integrate technology in educational practice,” Computers & Education, vol. 50, no. 3, pp. 1084-1091, 2008.

[30] D.R. Compeau, and C.A. Higgins, “Computer self-efficacy: Development of a measure and initial test,” MIS Quarterly, pp. 189-211, 1995.

[31] S.A. Nikou, and A.A. Economides, “The impact of paper-based, computer-based and mobile-based self-assessment on students’ science motivation and achievement,” Computers in Human Behavior, vol. 55, pp. 1241-1248, 2016.

[32] L.A. Annetta, J. Minogue, S.Y. Holmes, and M.T. Cheng, “Investigating the impact of video games on high school students’ engagement and learning about genetics,” Computers & Education, vol. 53, no. 1, pp. 74-85, 2009.

[33] E.W.T. Ngai, J. K. L. Poon, and Y.H.C. Chan, “Empirical examination of the adoption of WebCT using TAM,” Computers & Education, vol. 48, no. 2, pp. 250-267, 2007.

[34] T.Teo, and C. Beng Lee, “Explaining the intention to use technology among student teachers: An application of the Theory of Planned Behavior (TPB),” Campus-Wide Information Systems, vol. 27, no. 2, pp. 60-67, 2010.

[35] T. Teo, and C. Beng Lee, C. Sing Chai, and S.L. Wong, “Assessing the intention to use technology among pre-service teachers in Singapore and Malaysia: A multigroup invariance analysis of the Technology Acceptance Model (TAM),” Computers & Education, vol. 53, no. 3, pp. 1000-1009, 2009.

[36] J.Y.L. Thong, W. Hong, and K.Y. Tam, “Understanding user acceptance of digital libraries: what are the roles of interface characteristics, organizational context, and individual differences?” International journal of human-computer studies, vol. 57, no. 3, pp. 215-242, 2002.

[37] M.A. Camilleri, and A.C. Camilleri, “Digital learning resources and ubiquitous technologies in education,” Technology, Knowledge and Learning, vol. 22, no. 1, pp. 65- 82, 2017.

[38] D.Y. Lee, and M.R. Lehto, “User acceptance of YouTube for procedural learning: An extension of the Technology Acceptance Model.” Computers & Education, vol. 61, pp. 193-208, 2013.

[39] T. Teo, and P. Van Schalk, “Understanding technology acceptance in pre-service teachers: A structural-equation modeling approach,” The Asia-Pacific Education Researcher, vol. 18, no. 1, pp. 47-66, 2009.

[40] C. Smarkola, “Technology acceptance predictors among student teachers and experienced classroom teachers,” Journal of Educational Computing Research, vol. 37, no. 1, pp. 65-82, 2007.

[41] M.A. Camilleri, and A.C. Camilleri, “Measuring The Educators’ Behavioural Intention, Perceived Use And Ease Of Use Of Mobile Technologies,” In Wood, G. (Ed) Reconnecting management research with the disciplines: Shaping the research agenda for the social sciences (University of Warwick, September). British Academy of Management, UK, 2017.

[42] M. Turner, B. Kitchenham, P. Brereton, S. Charters, and D. Budgen, “Does the technology acceptance model predict actual use? A systematic literature review,” Information and Software Technology, vol. 52, no. 5, pp. 463-479, 2010.

[43] R.P. Bagozzi, and Y. Youjae, “On the evaluation of structural equation models,” Journal of the Academy of Marketing Science, vol. 16, no. 1, pp.74-94, 1988.

[44] M.A. Camilleri, and A.C. Camilleri, “The Technology Acceptance of Mobile Applications in Education,” In Sánchez, I.A. and Isaias, P. (Eds) 13th International Conference on Mobile Learning (Budapest, 11th April). pp41-48. International Association for Development of the Information Society, 2017.

[45] A. Colbert, N. Yee, and G. George, “The digital workforce and the workplace of the future,” Academy of Management Journal, vol. 59, no. 3, pp. 731-739, 2016.

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Tourism Futures: Targeting Customers in the Digital Age

This is an excerpt from: Camilleri’s latest book on Travel Marketing (2018)

How to Cite: Camilleri, M. A. (2018). Market Segmentation, Targeting and Positioning. In Travel Marketing, Tourism Economics and the Airline Product (Chapter 4, pp. 69-83). Springer, Cham, Switzerland.

The advances in technology have enabled many businesses to reach their potential customers by using digital and mobile applications.

Google, Facebook, Ebay and Amazon, among others are dominating digital marketing; and are pushing the entire field of advertising to new levels. The use of personal info, web-browsing, search history, geographic location, apps and eCommerce transactions have gone mainstream. For example, Google has begun using transaction records to prove that its ads are working, and are pushing people to make more online purchases. This allowed the technology giant to determine the effectiveness of its digital ad campaigns and to verify their conversion rates.

All individuals leave a “digital trail” of data as they move about in the virtual and physical worlds. This phenomenon is called, “data exhaust”. Initially, this term that was used to describe how Amazon.com has used predictive analytics as it suggested items to its customers. However, pre­dictive analytics cannot determine when and why individuals may decide to change their habitual behaviours, as the possibility of “one off” events must never be discounted. Yet, a firm with sufficient scarce resources could be in a position to exploit big data and analytics to improve its businesses operations.

For instance, Deloitte Consulting have developed a mobile app that has enabled Delta Airlines’ executives to quickly query their operations. For instance, when users touch an airport on a map, the system brings up additional data at their disposal. Executives could also drill further down to obtain granular information on staffing requirements. and customer service levels, as they identify and predict problems in their airline operations.

Nevertheless, business intelligence and predictive analytics could possibly raise a number of concerns. Many customers may be wary of giving their data to the businesses and their stakeholders. Very often, the technological advances anticipate legislation, and its deployment. These contingent issues could advance economic and privacy concerns that regulators will find themselves hard-pressed to ignore. Some academics argue that the digital market and its manipulation may be pushing the limits of consumer protection law. Evidently, society has built up a set of rules that are aimed to protect personal information. Another contentious issue is figuring out the value of data and its worth in monetary terms. In the past, companies could have struggled to determine the value of their business; including patents, trade secrets and other intellectual property.

Targeted Segmentation through Mobile Devices

The mobile is an effective channel to reach out to many users. Portable devices, including smart phones and tablets are surely increasing the productivities and efficiencies of individuals as well as organisations. This has led to the growth of mobile applications (apps). As a result, the market for advertising on mobile is still escalating at a fast pace. Moreover, there are niche areas as new applications are being developed for many purposes on different mobile platforms.

Recent advances in mobile communication and geo-positioning technologies have presented marketers with a new way how to target consumers. Location-targeted mobile advertising involves the provision of ad messages to mobile data subscribers. This digital technology allows marketers to deliver native ads and coupons that are customised to individual consumers’ tastes, geographic location and the time of day. Given the ubiquity of mobile devices, location-targeted mobile advertising are increasingly offering tremendous marketing benefits.

In addition, many businesses are commonly utilising applications, including browser cookies that track consumers through their mobile devices, as they move out and about. Very often, when internet users leave the sites they visited, the products or services they viewed will be shown to them again in retargeted advertisements, across different websites. Several companies are using browsing session data combined with the consumers’ purchase history to deliver “suitable” items that consumers like. There are also tourism businesses who are personalising their offerings as they collect, classify and use large data volumes on the consumers’ behaviours. As more consumers carry smartphones with them, they may be easily targeted with compelling offers that instantaneously pop-up on their mobile screens.

Furthermore, consumers are continuously using social networks which are indicating their geo-location, as they use mobile apps. This same data can be used to identify where people tend to gather. This information is valuable to brands as they seek to improve their consumer engagement and marketing efforts. Therefore, businesses are using mobile devices and networks to capture important consumer data. For instance, smart phones and tablets interact with networks and convey information on their users’ digital behaviours and physical movements to network providers and ISPs. These devices have become interactive through the proliferation of technologies, including; near-field communication (NFC). Basically, embedded chips in the customers’ mobile phones are exchanging data with the retailers’ items possessing such NFC tags. The latest iPhone, Android and Microsoft smartphones have already incorporated NFC ca­pabilities. The growth of such data-driven, digital technologies is surely adding value to the customer-centric marketing. The latest developments in analytics are enabling businesses to provide a deeper personalisation of content as they use socio-demographic and geo-data that new mobile technologies are capable of gathering.

For example, mobile service companies are partnering with local cinemas, in response to the location-targeted mobile advertising; as cinema-goers may inquire about movie information, and could book tickets, and select their seats through their mobile app. These consumers who are physically situated within a given geographic proximity of the participating cinemas may receive location-targeted mobile ads. The cinemas’ ads will inform prospects what movies they are playing and could explain how to purchase tickets through their smart phone. The consumers may also call the cinemas’ hotlines to get more information from a customer service representative. Besides location-targeted advertising, the mobile companies can also promote movie ticket sales via mobile ads that are targeted to individuals, according to their behaviour (not by location). Therefore, companies may direct their mobile-ad messages to those consumers who had previously responded to previous mobile ads (and to others who had already purchased movie tickets, in the past months). Moreover, the cinema companies can also promote movies via Facebook Messenger Ads if they logged in the companies’ websites, via their Facebook account. Mobile users may also receive instant message ads via pop-up windows whenever they log into the corporate site of their service provider.

It is envisaged that such data points will only increase in the foreseeable future, as the multi-billion dollar advertising monopolies are being built on big data and analytics that are helping businesses personalise immersive ads as they target individual customers. The use of credit card transactions is also complementing geo-targeting and Google Maps, with ads; as the physical purchases are increasingly demanding personalisation, fulfillment and convenience. There may be consumers and employees alike who out of their own volition, are willing to give up their data for value. Therefore, the businesses need to reassure them through concise disclosures on how they will use personal data. They should clarify the purpose of maintaining their consumer data, as they are expected to provide simple user controls to opt in and out of different levels of data sharing. This way, they could establish a trust-worthy relationship with customers and prospects.

Companies are already personalising their shopping experience based on the user situation and history. Tomorrow’s tourism businesses are expected to customise the user experiences of their mobile applications and web interfaces, according to the specific needs of each segment. Big data and analytics capabilities are increasingly allowing businesses to fully leverage their rich data from a range of new digital touchpoints and to turn them into high impact interactions. Those businesses that are able to reorient their marketing and product-development efforts around digital customer segments and behaviours will be in a position to tap into the hyper-growth that mobile, social media and the wearables markets are currently experiencing.

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The Technology Acceptance of Mobile Applications in Education

Dr Mark A. Camilleri from the University of Malta’s Department of Corporate Communication and Ms Adriana C. Camilleri, a PhD Candidate at the University of Bath (U.K.) have recently delivered a presentation of their latest empirical paper, entitled; The Technology Acceptance of Mobile Applications in Education during the 13th Mobile Learning Conference in Budapest, Hungary. More details on this highly indexed conference are available in this site: http://mlearning-conf.org/. An abstract of this paper is enclosed hereunder:

This paper explores the educators’ attitudes and behavioural intention toward mobile applications. Its research methodology has integrated previously tried and tested measures from ‘the pace of technological innovativeness’ and the ‘technology acceptance model’ to better understand the rationale for further investment in mobile learning technologies (m-learning). A quantitative study was carried out amongst two hundred forty-one educators to reveal their perceptions on their ‘use’ and ‘ease of use’ of mobile devices in their schools. A principal component analysis has indicated that these educators were committed to using mobile technologies. In addition, a stepwise regression analysis has shown that the younger teachers were increasingly engaging in m-learning resources. In conclusion, this contribution puts forward key implications for both academia and practitioners.

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Quality Education for Smart, Inclusive and Sustainable Growth

imagesThe promotion of quality education has re-emerged as an important policy objective across many countries during the past decade. For instance, the aims of Europe 2020 strategy (that was launched in 2010) were to improve the EU’s competitiveness and productivity that underpin a sustainable social market economy (EU, 2010 a,b). The strategy identified three priorities as the main pillars of this strategy:

  • Smart growth—developing an economy based on knowledge and innovation;
  • Sustainable growth—promoting a more resource efficient, greener and more competitive economy; and
  • Inclusive growth—fostering a high-employment economy delivering economic, social and territorial cohesion (Pasimeni & Pasimeni, 2015).

Significant investments have already been made across the globe to raise relevant competencies that help to improve social outcomes (e.g. social inclusion, social equity and social capital) since these are known to affect educational and labour market success.

In a similar vein, the fourth United Nations’ Sustainable Development Goal (SDG4) and its 10 targets represent an ambitious and universal agenda to develop better skills for better lives. Five of its 10 targets are concerned with improving the quality of education for individual children, young people and adults, and to give them better and more relevant knowledge and skills. During the last few decades; major progress has been made towards increasing access to education at all levels; from school readiness among young children through achieving literacy and numeracy at primary school, increasing enrolment rates in schools particularly for women and girls to equipping young adults with knowledge and skills for decent work and global citizenship (UNSDG4, 2015). In this light, the SDG4’s targets are the following (UNSDG4, 2015):

Quality education

By 2030, ensure that all girls and boys complete free, equitable and quality primary and secondary education leading to relevant and Goal-4 effective learning outcomes;

By 2030, ensure that all girls and boys have access to quality early childhood development, care and pre-primary education so that they are ready for primary education;

By 2030, ensure equal access for all women and men to affordable and quality technical, vocational and tertiary education, including university;

By 2030, substantially increase the number of youth and adults who have relevant skills, including technical and vocational skills, for employment, decent jobs and entrepreneurship;

By 2030, eliminate gender disparities in education and ensure equal access to all levels of education and vocational training for the vulnerable, including persons with disabilities, indigenous peoples and children in vulnerable situations;

By 2030, ensure that all youth and a substantial proportion of adults, both men and women, achieve literacy and numeracy;

By 2030, ensure that all learners acquire the knowledge and skills needed to promote sustainable development, including, among others, through education for sustainable development and sustainable lifestyles, human rights, gender equality, promotion of a culture of peace and non-violence, global citizenship and appreciation of cultural diversity and of culture’s contribution to sustainable development;

Build and upgrade education facilities that are child, disability and gender sensitive and provide safe, nonviolent, inclusive and effective learning environments for all;

By 2020, substantially expand globally the number of scholarships available to developing countries, in particular least developed countries, small island developing States and African countries, for enrolment in higher education, including vocational training and information and communications technology, technical, engineering and scientific programmes, in developed countries and other developing countries. By 2030, substantially increase the supply of qualified teachers, including through international cooperation for teacher training in developing countries, especially least developed countries and small island developing states (UNSDG4, 2015).

However, The Programme for International Student Assessment (PISA) the world’s most widely used global metric to measure the quality of learning outcomes, as well as its adult version, the Programme for the International Assessment of Adult Competencies (PIAAC), underlined that although many countries may have  their children in school; only a proportion of them achieve adequate levels of proficiency by the end of lower secondary education (PISA, 2012). This finding does not augur well for economic, social and sustainable development.

Bolder efforts are required to make even greater strides to achieve the sustainable development goal of quality education for all. A centralised educational policy may help to achieve the desired outcomes. Well-laid out curricula are capable of successfully developing the full potential of lifelong learners. In addition, the government’s policies of taxation and redistribution of income may also help to counteract inequalities in some segments of society.

The provision of quality education introduces certain mechanisms that equip people with relevant knowledge and skills that they need for today’s labour market. Active employment policies are required to help unemployed people find work. The overall objective of the employability programmes is the reintegration of jobseekers and the inactive individuals into the labour market as well as the provision of assistance to employed persons to secure and advance in their job prospects.

 

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Reconceiving CSR for Business and the Labour Market

cogent
This contribution maintains that it is in the private sector’s interest to actively participate in reconceiving education for societal well being. It posits that there are win-win opportunities for companies and national governments as they cultivate human capital. Indeed, companies can create synergistic value for both business and society. Such a strategic approach can result in new business models and cross-sector collaborations that will inevitably lead to operational efficiencies, cost savings and significant improvements to the firms’ bottom lines. The CSR initiatives in education can also help organisations to improve the recruitment and retention of talented employees. This paper has reported that employees want to be part of organisations that genuinely demonstrate their concern for society. There was mention of strategic philanthropic initiatives that manifest corporate behaviours that also satisfy much of the stakeholders’ aspirations. Organisations can always make use effective CSR communications to attract the best employees and talent pool from the labour market. Ideally, businesses ought to treat employees as internal customers as it is critical for their long term success. In a sense, the organisational culture and its commitment for CSR engagement can play an integral role, in this regard. In fact, CSR and environment sustainability issues are increasingly becoming ubiquitous practices in different contexts, particularly for the youngest work force.

This research indicated that there is a business case for corporate sustainable and responsible behaviours. Besides, minimising staff turnover, CSR may lead to systematic benefits including employee productivity, corporate reputation and operational efficiencies. This implies that CSR is an antecedent for an optimal financial performance (towards achieving profitability, increasing sales, return on investment et cetera). At the same time, the businesses’ CSR engagement could create significant value to society as well. The corporations’ involvement in setting curricula and relevant course programmes may also help to improve the effectiveness of education systems across many contexts. It is imperative that businesses become key stakeholders in the provision of education and training. There is a possibility that CSR programmes could reconnect the businesses’ economic success with societal progress. Proactive companies who engage in strategic CSR behaviours could uncover new business opportunities (Lauring and Thomsen, 2008) and achieve competitive advantage (Porter and Kramer, 2006). Indeed, businesses are in a position to nurture employees by enhancing their knowledge and skill sets. This will inevitably lead to more competent staff and to significant improvements in work productivity among other benefits.

CSR can be reconceived strategically for business and educational outcomes. This research has given specific examples of how different organisations were engaging in responsible behaviours with varying degrees of intensity and success. It has identified cost effective and efficient operations. It reported measures which were enhancing the human resources productivity. Other practices sought to engage in philanthropic practices and stewardship principles. Indeed there are positive outcomes that represent a leap forward for the CSR agenda. This contribution reiterated that it is in the businesses’ self-interest to maintain good relations with employees. Evidently, there is more to CSR than public relations, greenwashing and posturing behaviours. Businesses need to engage with stakeholders and to forge long lasting relationships with them. Corporate responsible behaviours bring reputational benefits, enhance the firms’ image among external stakeholders and often lead to a favourable climate of trust and cooperation within the company itself (Herzberg et al., 2011). A participative leadership will also boost the employees’ morale and job satisfaction. This will also lead to lower staff turnover rates and greater productivity levels in workplace environments (Fida et al., 2014). Notwithstanding, there are many businesses that still need to align their organisational culture and business ethos in order to better embrace responsible behavioural practices.

Governments also have an important role to play. They can take an active leading role in triggering corporate responsible behaviours in education. Greater efforts are required by policy makers, the private sector and other stakeholders. The governments could give reasonable incentives (through financial resources in the form of grants or tax relief) and enforce regulation in certain areas where responsible behaviour is necessary. They need to maintain two-way communication systems with stakeholders. This paper posited that the countries’ educational outcomes and their curriculum programmes should better respond to the employers’ requirements. Therefore, educational programmes ought to instil students with relevant knowledge and skills that are really required by business and industry. Several governments, particularly those from developing nations ought to step up with their commitment to develop new solutions to help underprivileged populations and subgroups. New solutions could better address the diverse needs of learners and prospective employees. This research indicated that there is scope for governments to work in collaboration with corporations in order to improve the employability of tomorrow’s human resources.
Research Limitations and Future Research Avenues

It must be recognised that there are various forms of businesses out there, hailing from diverse sectors and industries. In addition, there are many stakeholder influences, which can possibly affect the firms’ level of social responsibility toward education. It is necessary for governments to realise that they need to work alongside business practitioners in order to reconceive education and life-long learning for all individuals in society. The majority of employers that were mentioned in this research were representative of a few corporations that are based in the most developed economies. Yet, there could be different CSR practices across diverse contexts. Future research could consider different sampling frames, methodologies and analyses which may yield different outcomes.

This contribution has put forward the ‘shared value’ approach in education (Camilleri, 2014; Porter and Kramer, 2011). It is believed that since this relatively ‘new’ proposition is relatively straightforward and uncomplicated, it may be more easily understood by business practitioners themselves. In a nutshell, this synergistic value notion requires particular focus on the human resources’ educational requirements. At the same time, ‘shared value’ also looks after the stakeholders’ needs (Camilleri, 2015). This promising concept could contribute towards bringing long term sustainability by addressing economic and societal deficits in the realms of education. A longitudinal study in this area of research could possibly investigate the long term effects of involving the business and industry in setting curriculum programmes and relevant learning outcomes. Presumably, shared value can be sustained only if there is a genuine commitment to organisational learning for corporate sustainability and responsibility, and if there is the willingness to forge long lasting relationships with key stakeholders.

Recommendations
The corporations’ social responsibility in the provision of education has potential to create shared value as it opens up new opportunities for business and society. There are competitive advantages that may arise from nurturing human resources (McKenzie and Woodruff, (2013), Kehoe and Wright (2013) and Hunt and Michael, (1983). As firms reap profits and grow, they can generate virtuous circles of positive multiplier effects. In a way, businesses could create value for themselves as well as for society by sponsoring educational institutions, specific courses and individuals. In conclusion, this contribution puts forward the following recommendations to foster an environment where businesses are encouraged to become key stakeholders in education:

• Promotion of business processes that bring economic, social and environmental value through the encouragement of innovative and creative approaches in continuous professional development and training in sustainable and responsible practices; including socially responsible investing (SRI), responsible supply chain management, the circular economy, responsible procurement of sustainable products, consumer awareness of sustainability / eco labels, climate change and the environmental awareness;

• Enhancement of collaborations and partnership agreements between governments, business and industry leaders, trade unions and civil society. There should be an increased CSR awareness, continuous dialogue, constructive communication and trust among all stakeholders.

• National governments ought to create regulatory frameworks which encourage and enable the businesses’ participation in the formulation of educational programmes and their curricula.

• Policy makers should ensure that there are adequate levels of performance in areas such as employee health and safety, suitable working conditions and sustainable environmental practices among business and industry.

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Top US Corporate Citizenship Issues

In its latest quarterly magazine the Boston College Centre for Corporate Citizenship (BCCC) has reiterated how community involvement activities can contribute to achieve corporate goals – particularly, when they are aligned with the company’s business context and the interests of its stakeholders. Companies are becoming increasingly adept at tying employee volunteer and corporate giving programmes to their business strategy. Interestingly, BCCC (2015) noted that many businesses have proritised community involvement projects, including; K12 education, youth programmes and health and wellness programmes among others. These social issues have featured as the top priorities for businesses, as evidenced in BCCC’s (2015) Table. In 2009 and 2011 the top issues were more focused on environmental matters.

The inclusion of health in the top three social goals implies that lately there is more concern amongst US citizens regarding the rising cost of health care. In 2015, the U.S. has spent 17% of its gross domestic product on health care. This figure is higher than any other developed nation, and is projected to reach nearly 20 percent by 2024.

bccc

Unsurprisingly, science, technology, engineering and math (STEM) education is also an area that is receiving increased investments from business communities. According to BCCC’s (2015) study, nearly 40% of companies are focusing on STEM education in their community involvement programmes. These efforts ensure a future pipeline of talent and skills. In fact, OECD (2014) anticipated that there will be a 17 per cent increase in STEM related jobs between 2014 and 2024 (OECD, 2014).

Arguably, businesses are putting food where their mouth is. As they focus their competences and resources in the areas where they can do the most good, there is potential for them to achieve greater returns on their discretionary investments. At the same time, they close the skill gaps and mismatches in their labour market (Camilleri and Camilleri, 2015).

References:

BCCC (2015). The Corporate Citizen, Issue 14 (Fall 2015) Boston College Center for Corporate Citizenship https://bc-ccc.uberflip.com/i/571714-corporatecitizen-issue14

Camilleri, M.A.  and Camilleri, A. (2015). Education and social cohesion for economic growth, International Journal of Leadership in Education, DOI: 10.1080/13603124.2014.995721

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Corporate Social Responsibility for Business and Educational Outcomes

trngExcerpt from one of my recent chapters, entitled;

“Re-conceiving Corporate Social Responsibility Programmes for Education”

 

During their learning journey, individuals acquire knowledge and skills that ought to be relevant for their career endeavours. The provision of quality education and its assurance is the responsibility of national governments. Yet, business and industry also offer training to human resources that supplements formal education. Very often, educators are expected to respond to challenging issues such as skill shortages and mismatches where candidates lack certain competencies although they attended compulsory education (Allen and De Weert, 2007). Their knowledge and skills may be too deep to bridge through corporate training sessions. Perhaps, there is an opportunity for global businesses to compensate for this deficiency in the education (Gibb, 1993). Corporations can shift their operations where it is viable for them to tap qualified employees. However, the constraints on their growth can be halted by the broad impact of inadequate education and training in some industries or regions. In this light, this chapter contends that big businesses may become key players in addressing unmet needs in education. Several companies have the resources and the political influence to help improve educational outcomes; which will in turn help them cultivate local talent. Leading businesses are already devising corporate social responsibility (CSR) programmes that are actively supporting education across many contexts.

Therefore, this chapter redefines the private sector’s role in the realms of education. It posits that there are win-win opportunities for companies and national governments as they nurture human capital. Indeed, companies can create synergistic value for both business and society (Camilleri, 2015a). In the main, such a strategic approach may result in new business models and cross-sector collaborations that will inevitably lead to operational efficiencies, cost savings and significant improvements to the firms’ bottom lines (Pearce and Doh, 2012; Porter and Kramer, 2011). Notwithstanding, this contribution suggests that the businesses’ involvement in setting curricula may also help to improve the effectiveness of education systems in many contexts (Azevedo, Apfelthaler and Hurst, 2012; Seethamraju, 2012). Businesses can become key stakeholders in aligning educational programmes with their human capital requirements in the job market (Walker and Black, 2000). There is a possibility that their CSR programmes reconnect their economic success with societal progress.

Corporate Social Responsibility and Human Resources Management

Many companies are gaining a high reputation in corporate social and responsibility. While the cause marketing of the past primarily targeted consumers in sales transactions, today’s cause marketing is often concerned with the company’s strongest ambassadors — its employees (Kotler and Lee, 2008). Undoubtedly, businesses are contributing to the well-being of their human resources and the surrounding communities. Yet, other firms may resort to CSR and greenwashing to generate publicity and positive impressions among stakeholders (Visser, 2011; Jahdi and Acikdilli, 2009). Many academics, argue that the most successful CSR strategy is to align a company’s social and environmental activities with its business purpose and values (Visser, 2011; Porter and Kramer, 2011). Responsible actions have the power to reconceive the organisations’ purpose and values toward society. The first step towards developing a CSR mentality is to re-define the principles of the company. Arguably, the role of senior management is crucial in instilling an ethos for genuine CSR behaviours among employees.

Businesses know that prospective employees consider a variety of factors as they evaluate careers. Some individuals value financial incentives, including salary, bonus potential and benefits (Gerhart and Fang, 2014; Bloom and Milkovich, 1998). Others may focus on professional development, advancement opportunities and location (Kehoe and Wright, 2013; Hunt and Michael, 1983). However, only recently multinational companies seem to realise that through CSR they can better engage with their employees (Bhattacharya, Sen and Korschun, 2008). Evidently, CSR can provide incentives to employees that may potentially be even more alluring than money (Branco and Rodrigues, 2006).

Socially Responsible HRM affects employee task performance and extra-role helping behaviour (Shen and Benson, 2014; Korschun, Bhattacharya and Swain, 2014). In fact, their empirical results indicated that CSR that is directed toward employees is an indirect predictor of individual task performance and extra-role helping behaviour. Another study by Deloitte (2004) has yielded very similar results. 72% of US respondents indicated that they would opt to work for a company that also supports charitable causes; if they had to choose between two jobs offering the same location, job description, pay, and benefits. According to this study, the majority of the youngest survey participants have indicated that their decision to work for their current employer was based on company culture or reputation (Pfeffer, 2007; Deloitte, 2004). Evidently, these respondents also valued the opportunities for growth and development as well as their salary and benefits package. This Deloitte study has indicated that the corporate social responsibility agenda will remain relevant for tomorrow’s business leaders. Apparently, the youths’ generic characteristics may bring distinct CSR behaviours (Pomering and Dolnicar, 2009). Young people often place high importance on making a positive impact on society. Very often, organisations are capitalising on corporate influence on social trends including sport activities (Smith and Westerbeek, 2007). Such a viewpoint could encourage an examination of the overlaps between the social responsibilities of sport and business.

These findings seem to suggest that employees want to belong to an organisation that stands for more than financial performance (Korschun et al., 2014; Vanhamme, Lindgreen, Reast and van Popering, 2012; Tang, Hull and Rothenberg, 2012). Employees are attracted by companies that are truly CSR-oriented. In addition, the businesses’ genuine intentions and goodwill can help to improve the brands’ image among stakeholders. Thus, even if employees do participate in CSR initiatives, they still want to be associated with an organisation that cares about its social impact (Shen and Benson, 2014). Therefore, it is in the companies’ self-interest to underline their CSR performance during events that are aimed to attract top talent. Apparently, more companies are realising that CSR is a great opportunity to engage with employees and to illustrate their commitment to the community at large.

 

Citation: Camilleri, M.A. (2015) Re-conceiving CSR Programmes for Education. In Vertigans, S. & Idowu, S.O., Corporate Social Responsibility: Academic Insights and Impacts, Springer (Forthcoming).


 

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