Investigating the Association between Employee Silence and Perceived Organizational Support via Data Mining

Year 2020, Volume: 4 Issue: 2, 123 - 137, 31.12.2020

Volkan Yüncü , Üzeyir Fidan

https://doi.org/10.26650/acin.801398

Abstract

Modeling human behavior in distinctive contexts is of vital importance today, especially in research in the fields of marketing and management. From a management perspective, modeling employee behavior strengthens decision-makers’ hands in numerous areas such as workforce planning and management. Comprehensive employee profiles obtained offer business organizations extremely important strategic gains, especially sustainable competitive advantage. This study is the first attempt to model the relationship between employee silence behavior and perceived organizational support through data mining techniques, and it aims to extract employee profiles accordingly. Evaluating these two important phenomena within such a relational framework opens a novel door for organizational behavior researchers. The Association Rule Mining technique was applied to achieve knowledge discovery from the data obtained through two scales. Within the research, the rules above a threshold value of 0.50 were evaluated to make the associations representing the employee profiles more meaningful. Accordingly, firstly, the association rules between the factors of the organizational silence scale were evaluated and seven rules were obtained. Next, the perceived organizational support factor was included in the model, and how it affected the obtained association rules was examined. In this manner, ten association rules formed by the factors of the two scales were determined. The inclusion of the perceived organizational support factor revealed quite striking relationships. Especially, an association of over 80% observed in the first five rules enabled the discovery of hidden patterns in terms of determining employee profiles. These valuable inferences obtained through this study reveals the importance of utilizing data mining techniques for future profile extraction studies.

Keywords

Employee Silence, Perceived Organizational Support, Data Mining, Apriori Algorithm, Association Rule Mining

Çalışan Sessizliği ve Algılanan Örgütsel Destek Arasındaki İlişkinin Veri Madenciliği ile İncelenmesi

Abstract

İnsan davranışının kendine özgü bağlamlarda modellenmesi bugün özellikle pazarlama ve yönetim alanlarında yapılan araştırmalarda hayati önem taşımaktadır. Yönetim perspektifinden bakıldığında, çalışan davranışının modellenmesi karar vericilerin iş gücü planlaması ve yönetimi gibi pek çok konuda elini güçlendirmektedir. Elde edilen kapsamlı çalışan profilleri işletmelere başta sürdürülebilir rekabet üstünlüğü olmak üzere son derece önemli stratejik kazanımları sunmaktadır. Bu çalışma, çalışan sessizliği davranışı ile algılanan örgütsel destek arasındaki ilişkiyi veri madenciliği teknikleri aracılığıyla modellemeye yönelik öncül bir girişimdir ve bu bağlamda çalışan profili çıkarımı yapılmasını amaçlamaktadır. Bu iki önemli olgunun böyle bir ilişkisel bir çerçevede ele alınması örgütsel davranış araştırmacı için yeni bir kapı aralamaktadır. Çalışma kapsamında kullanılan ölçekler yardımıyla elde edilen verilerden bilgi keşfi yapabilmek için birliktelik kuralları analizi uygulanmıştır. Araştırma kapsamında çalşan profillerini temsilen elde edilen birlikteliklerin daha anlamlı olabilmesi için 0,50 eşik değeri üzerindeki kurallar değerlendirilmiştir. Bu doğrultuda, öncelikle örgütsel sessizlik ölçeğinin faktörleri arasındaki birliktelik kuralları değerlendirilmiş ve yedi kural elde edilmiştir. Daha sonra, algılanan örgütsel destek faktörü modele dahil edilerek elde edilen birliktelik kurallarını nasıl etkilediği incelenmiştir. Böylece her iki ölçeğin faktörlerinin bir arada oluşturduğu on birliktelik kuralı belirlenmiştir. Algılanan örgütsel destek faktörünün dahil olmasıyla araştırma için oldukça çarpıcı ilişkiler ortaya çıkarılmıştır. Özellikle ilk beş kuralda gözlemlenen %80 üzerinde birliktelik ilişkisi, çalışan profillerinin belirlenmesi açısından gizli kalmış örüntülerin keşfedilmesini sağlamıştır. Çalışma kapsamında elde edilen bu değerli çıkarımlar gelecekte yapılacak profil çıkarımı çalışmaları için veri madenciliği tekniklerinin kullanımının önemini ortaya koymaktadır.

Keywords

Çalışan Sessizliği, Algılanan Örgütsel Destek, Veri Madenciliği, Apriori Algoritması, Birliktelik Kuralları Analizi

References

• Aggarwal, C. (2015). Data mining: the textbook. Springer. doi: 10.1007/978-3-319-14142-8
• Agrawal, R., & Srikant, R. (1994). Fast algorithms for mining association rules. In Proc. 20th int. conf. very large data bases, VLDB (Vol. 1215, pp. 487-499).
• Akçin, K. vd. (2017). Effect of Perceived Organizational Support On Organizational Silence and Task Performance: A Study on Academicians. Journal of Global Strategic Management , vol.11, pp.35-44.
• Allen, D.G., Shore, L.M., ve Griffeth, R.W. (2003) The role of perceived organizational support and supportive human resource practices in the turnover process. Journal of Management, 29, 99–118.
• Beheshtifar vd. (2012). Destructive role of employee silence in organizational success, International Journal of Academic Research in Business and Social Sciences, 2 (11): 275-282.
• Beheshtifar, Malikeh & Borhani, Hossein & Nekoei-Moghadam, Mahmood. (2012). Destructive Role of Employee Silence in Organizational Success. International Journal of Academic Research in Business and Social Sciences. 2.
• Bramer, M. (2007). Principles of data mining (Vol. 180). London: Springer. ISBN : 978-1-4471-7306-9
• Chen, Zhixia & Eisenberger, Robert & Johnson, Kelly & Sucharski, Ivan & Aselage, Justin. (2009). Perceived Organizational Support and Extra-Role Performance: Which Leads to Which?. The Journal of social psychology. 149. 119-24. 10.3200/SOCP.149.1.119-124.
• Choi, J. H., & Park, H. C. (2008). Comparative study of quantitative data binning methods in association rule. Journal of the Korean Data and Information Science Society, 19(3), 903-911.
• Chou, S. Y., & Chang, T. (2017). Employee silence and silence antecedents: A theoretical classification. International Journal of Business Communication. https://doi.org/10.1177/ 2329488417703301.
• Çınar, O., Karcıoğlu, F. & Alioğulları, Z. (2013). The relationship between organizational silence and organizational citizenship behavior: A survey study in the province of Erzurum, Turkey. Procedia - Social and Behavioral Sciences. 99. 314-321. 10.1016/j.sbspro.2013.10.499.
• Donaghey, J., Cullinane, N., Dundon, T., & Wilkinson, A. (2011). Reconceptualising employee silence: problems and prognosis. Work, Employment and Society, 25(1), 51–67. https://doi.org/10.1177/0950017010389239
• Dyne, L. V., Ang, S., & Botero, I. C. (2003). Conceptualizing employee silence and employee voice as multidimensional constructs. Journal of management studies, 40(6), 1359-1392. https://doi.org/10.1111/1467-6486.00384
• Eisenberger, R. L., Fasolo, P., & Davis‐LaMastro, V. (1990). Perceived organizational support and employee diligence, commitment, and innovation. The Journal of Applied Psychology, 75, 51–59.
• Eisenberger, R., & Stinglhamber, F. (2011). Perceived organizational support: Fostering enthusiastic and productive employees. Washington, DC: American Psychological Asso- ciation. http://dx.doi.org/10.1037/12318-000
• Eisenberger, R., Huntington, R., Hutchison, S., & Sowa, D. (1986). Perceived organizational support. Journal of Applied Psychology, 71, 500–507. http://dx.doi.org/10.1037/0021- 9010.71.3.500
• Han, J., Pei, J., & Kamber, M. (2011). Data mining: concepts and techniques. Elsevier. ISBN 13: 978-1-55860-901-3 ISBN 10: 1-55860-901-6
• Hayton, J. C., Carnabuci, G., & Eisenberger, R. (2012). With a little help from my colleagues: A social embeddedness approach to perceived organizational support. Journal of Organizational Behavior, 33, 235–249. http://dx.doi.org/10.1002/job.755
• Hirschman, A. O. (1970). Exit, voice, and loyalty: Reponses to decline in firms, organizations, and states. Cambridge, MA: Harvard University Press.
• Huang X, Van de Vliert E ve Van Der Vegt G (2005). Breaking the silence culture: stimula- tion of participation and employee opinion withholding cross-nationally. Management and Organization Review 1(3): 459–482.
• Huang, X., Van V., Evert, V. (2005), breaking the silence culture: stimulation of participation and employee opinion withholding cross-nationally, management and organization review, Vol.1, No.3, PP. 1740-8776.
• Jaweria Khalid & Jaleel Ahmed (2016) Perceived organizational politics and employee silence: supervisor trust as a moderator, Journal of the Asia Pacific Economy, 21:2, 174-195, DOI: 10.1080/13547860.2015.1092279
• Karakaş, Ayhan. (2019). The relationship between perceived supervisor support and the aspects of organizational silence. 8. 1-19.
• Kurtessis, J. N., Eisenberger, R., Ford, M. T., Buffardi, L. C., Stewart, K. A., & Adis, C. S. (2017). Perceived organizational support a meta-analytic evaluation of organizational support theory. Journal of Management, 43, 1854–1884. http://dx.doi.org/10.1177/ 0149206315575554
• LaPiere, R. T. (1934). Attitudes vs. actions. Social forces, 13(2), 230-237. doi: 10.2307/2570339
• Levinson, H. (1965). Reciprocation: The relationship between man and organization. Admin- istrative Science Quarterly, 9, 370–390. http://dx.doi.org/10.2307/2391032
• Linoff, G. S., & Berry, M. J. (2011). Data mining techniques: for marketing, sales, and customer relationship management. John Wiley & Sons. ISBN: 978-0-470-65093-6
• Liu, B., Hsu, W., & Ma, Y. (1998). Integrating classification and association rule mining. In KDD (Vol. 98, pp. 80-86).
• Milliken FJ, Morrison EW, Hewlin PF. (2003). An exploratory study of employee silence: Issues that employees don’t communicate upward and why. Journal of Management Studies, 40, 1453–1476.
• Morrison EW, Milliken FJ. (2000). Organizational silence: A barrier to change and devel- opment in a pluralistic world. Academy of Management Review, 25, 706–725.
• Olson, D. L., & Delen, D. (2008). Advanced data mining techniques. Springer Science & Business Media. ISBN: 978-3-540-76916-3 e-ISBN: 978-3-540-76917-0
• Pedro Neves Robert Eisenberger (2014). Perceived organizational support and risk taking, Journal of Managerial Psychology, Vol. 29 Iss 2 pp. 187-205 http://dx.doi.org/10.1108/JMP-07-2011-0021
• Pinder CC. &Harlos KP. (2001). Employee silence: Quiescence and acquiescence asresponses to perceived injustice. Research in Personnel and Human Resources Management, 20, 331–369.
• Rhoades, L., & Eisenberger, R. (2002). Perceived organizational support: A review of the literature. The Journal of Applied Psychology, 87, 698–714.
• Schlenker, B. R. & Weigold, M. F. (1989). ‘Self-identification and accountability’. In Giacalone, R. A. and Rosenfeld, P. (Eds), Impression Management in the Organization. Hillsdale, NJ: Erlbaum, 21–43.
• Shanock, L. R., Eisenberger, R., Heggestad, E. D., Malone, G., Clark, L., Dunn, A. M., Kirkland, J., & Woznyj, H. (2019). Treating employees well: the value of organizational support theory in human resource management. The Psychologist-Manager Journal. Advance online publication. http://dx.doi.org/10.1037/mgr0000088
• Shore, L. M., & Shore, T. H. (1995). Perceived organizational support and organizational justice. In R. S. Cropanzano, & K. M. Kacmar (Eds.). Organizational politics, justice and support: Managing the social climate of the workplace (pp. 149–164). Wesport, CT: Quorum.
• Singh, B. S., & Malhotra, M. (2015). The mediating role of trust in the relationship between perceived organizational support and silence.International Journal of Scientific and Research Publications, 5(9), 1-10.
• Tangirala, S., & Ramanujam, R. (2008). Employee silence on critical work issues: The cross level effects of procedural justice climate. Personnel Psychology, 61, 37–68.
• Tucker, S., Chmiel, N., Turner, N., Hershcovis, M. S. ve Stride, C. B. (2008). Perceived organizational support for safety and employee safety voice: The mediating role of co-worker support for safety. Journal of Occupational Health Psychology, 13(4), 319-330.
• Van Dyne, L., Ang, S., & Botero, I. C. (2003). Conceptualizing employee silence and employee voice as multidimensional constructs. Journal of Management Studies, 40(6), 1359–1392. https://doi.org/10.1111/1467-6486.00384
• Van Dyne, L., Ang, S., & Botero, I. C. (2003). Conceptualizing employee silence and employee voice as multidimensional constructs. Journal of Management Studies, 40(6), 1359–1392.
• Wang, H., & Wang, S. (2010). Mining incomplete survey data through classification. Knowledge and information systems, 24(2), 221-233. https://doi.org/10.1007/s10115-009-0245-8
• Wang, Y. & Hsieh, H. (2013). Organizational ethical climate, perceived organizational support and employee silence: A cross-level investigation. Human Relations, 66(6), 783-802.
• Whiteside, D., & Barclay, L. (2012). Echoes of silence: Employee silence as a mediator between overall justice and employee outcomes. Journal of Business Ethics, 116, 251-266. doi:10.1007/s10551-012-1467-3
• Yu, Y. & Liu, Q. (2016). The effect of psychological capital and organizational support on ınnovational behavior and silence behavior of technical ınnovation personnel in strategic emerging industry. American Journal of Industrial and Business Management, 6, 732-740. doi: 10.4236/ajibm.2016.66067.
• Yüncü, V. & Koparal, C. (2017). Fundamental paradigms for corporate reputation, economics and applied informatics, Dunarea de Jos University of Galati, Faculty of Economics and Business Administration, issue 2, pages 60-65
• Yüncü, V. & Fidan, Ü. (2019). Revisiting the relationship between organizational silence and perceived organizational support through association rule mining. (29-30 June 2019) 5th International EMI Entrepreneurship & Social Sciences Congress (s.153). Gostivar/N.Macedonia
• Zehir, C. & Erdogan, E. (2011). The association between organizational silence and ethical leadership through employee performance, Procedia Social and Behavioral Sciences, 24: 1389-1404.
• Zhang, N., & Lu, W. F. (2007). An efficient data preprocessing method for mining customer survey data. In 2007 5th IEEE International Conference on Industrial Informatics (Vol. 1, pp. 573-578). IEEE. doi: 10.1109/INDIN.2007.4384821