The effect of lean tool on research culture and research performance in Indonesia’s higher education institutions
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Author(s)Farida FaridaLink to ORCID Index: https://orcid.org/0000-0002-8141-7152
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Ahmad Badawi SaluyLink to ORCID Index: https://orcid.org/0000-0002-5880-4269
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Kasmir KasmirLink to ORCID Index: https://orcid.org/0000-0003-3365-4628
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Lenny Christina NawangsariLink to ORCID Index: https://orcid.org/0009-0000-4052-4640
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DOIhttp://dx.doi.org/10.21511/kpm.08(1).2024.07
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Article InfoVolume 8 2024, Issue #1, pp. 91-103
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71 Downloads
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Creative Commons Attribution 4.0 International License
Quality Assurance in higher education is a lean tool to improve the quality and performance of HEIs, including lecturer research performance. This study examines the effect of implementing Quality Assurance in higher education as a lean tool on the research culture and research performance of lecturers at Indonesia’s private HEIs. The data represent respondents’ perceptions of the research variable indicators. 184 questionnaires were suitable for processing. Data were collected from 184 lecturers from approximately 25 private HEIs in Jakarta, Indonesia. A 5-point Likert scale was used to measure indicators of research variables. Statistical data analysis was carried out using Structural Equation Modeling with the Smart-PLS ™ program. The results show that Quality Assurance as a lean tool has a significant impact on research performance (β = 0.643; p = 0.000) and research culture (β = 0.361; p = 0.000). Research culture affected research performance significantly (β = 0.281; p = 0.000), and research culture significantly mediates the effect of Quality Assurance as a lean tool on the research performance (β = 0.102; p = 0.010), and the effect is strong (Ѵ = 0.181). Research findings reveal that the successful implementation of Quality Assurance as a lean tool is determined more by organizational readiness than individual readiness; this is reflected in the existence of effective research centers. An effective research center will support the standardization of research processes through continuous improvement so that lecturers behave more actively in scientific activities and perform research more productively.
- Keywords
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JEL Classification (Paper profile tab)I23, D83
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References65
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Tables8
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Figures2
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- Figure 1. Implementation of QA in HE as a lean tool to research performance (Model 1)
- Figure 2. Implementation of QA in HE as a lean tool to research performance (Model 2)
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- Table 1. Indicators of QA as a lean tool
- Table 2. Research culture indicators
- Table 3. Research performance indicators
- Table 4. Construct reliability and validity
- Table 5. HTMT value in discriminant validity
- Table 6. New HTMT value in discriminant validity
- Table 8. Predictive relevance (Q2)
- Table 9. Model fit
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- Adapa, P. K. (2013). Strategies and Factors Effecting Internationalization of University Research and Education.
- Alefari, M., Salonitis, K., & Xu, Y. (2017). The role of leadership in implementing lean manufacturing. Procedia CIRP, 63, 756-761.
- Antony, J. (2014). Readiness factors for the Lean Six Sigma journey in the higher education sector. International Journal of Productivity and Performance Management, 63(2), 257-264.
- Anwar, R. (2014). The Secret to Making Operations More Effective and Efficient (In Indonesian).
- Ardimen, A., & Gustina, G. (2018). Penguatan Budaya Meneliti Melalui Pembelajaran Berbasis Riset Di Perguruan Tinggi [Strengthening Research Culture Through Research-Based Learning in Higher Education]. TA’DIB, 21(2). (In Indonesian).
- Balzer W. K., Francis, D. E., Krehbiel, T. C., & Shea, N. A. (2016). A review and perspective on Lean in higher education. Quality Assurance in Education, 24(4), 442-462.
- Balzer, W. K. (2020). Lean Higher Education: Increasing the Value and Performance of University Process. Routledge: Productivity Press.
- Bates, R. A., & Holton, E. F. (1995). Computerized performance monitoring: A review of human resource issues. Human Resource Management Review, 5(4), 267-288.
- Bergmiller, G. G., & Mccright, P. R. (2009). Are Lean and Green Programs Synergistic? Proceedings of the 2009 Industrial Engineering Research Conference (pp. 1155-1160).
- Bortolotti, T., Boscari, S., & Danese, P. (2015). Successful lean implementation: Organizational culture and soft lean practices. International Journal of Production Economics, 160, 182-201.
- Broström, A. (2019). Academic breeding grounds: Home department conditions and early career performance of academic researchers. Research Policy, 48(7), 1647-1665.
- Cadden, T., Millar, K., Treacy, R., & Humphreys, P. (2020). The mediating influence of organisational cultural practices in successful Lean Management Implementation. International Journal of Production Economics, 229, 107744.
- Campbell, J. P., Mchenry, J. J., & Wise, L. L. (1990). Modeling Job Performance In a Population of Jobs. Personnel Psychology, 43(2), 313-575.
- Chen, Y., Gupta, A., & Hoshower, L. (2006). Factors That Motivate Business Faculty to Conduct Research: An Expectancy Theory Analysis. Journal of Education for Business, 81(4), 179-189.
- Chin, W. W. (1998). The Partial Least Squares Approach to Structural Equation Modeling. In G. A. Marcoulides (Ed.), Modern methods for business research (pp. 295-336). University of Houston.
- Conti, A., Denas, O., & Visentin, F. (2014). Knowledge specialization in Ph.D. Student Groups. IEEE Transactions on Engineering Management, Forthcoming (pp. 52-67).
- Cua, K. O., Mckone, K. E., & Schroeder, R. G. (2001). Relationships between implementation of TQM, JIT, and TPM and manufacturing performance. Journal of Operations Management, 19(6), 675-694.
- Department of Trade and Industry/Department for Education and Employment (DTI/DfEE). (2001). Opportunity for All in a World of Change: A White Paper on Enterprise, Skills and Innovation. London: HMSO.
- Eldor, L., & Harpaz, I. (2016). A process model of employee engagement: The learning climate and its relationship with extra-role performance behaviors. Journal of Organizational Behavior, 37(2), 213-235
- Emiliani, M. L. (2004). Improving business school courses by applying lean principles and practices. Quality Assurance in Education, 12(4), 175-187.
- Engebretsen, E., Heggen, K., & Eilertsen, H. A. (2012). Accreditation and Power: A Discourse Analysis of a New Regime of Governance in Higher Education. Scandinavian Journal of Educational Research, 56(4), 401-417.
- Etzkowitz, H., & Kloftten, M. (2005). The Innovating Region: Toward a Theory of Knowledge-Based Regional Development. R&D Management, 35(3), 243-255.
- Evans, L. (2007). Developing research cultures and researchers in HE: the role of leadership. In Annual Conference of the Society for Research into Higher Education (SRHE).
- Farida, F., Prabowo, H. A, & Vidayanti, D. (2019). Evaluation of the foster program as an effort to accelerate the implementation of the quality assurance system in Indonesian private university. ACADEMIA, 16-17, 145-167.
- Farida, F., Prabowo, H. A., & Husnur, A. (2021). The readiness of human resources and organization in implementing total quality management (TQM) in Indonesia’s manufacturing industries. Journal of Engineering Research, 9(4A), 246-261.
- Garza-Reyes, J. A., Kumar, V., Chaikittisilp, S., & Tan, K. H. (2018) The effect of lean methods and tools on the environmental performance of manufacturing organisations, International Journal of Production Economics, 200, 170-180.
- Hadid, W., & Mansouri, S. A. (2014). The lean-performance relationship in services: A theoretical model. International Journal of Operations and Production Management, 34(6), 750-785.
- Hadid, W., Mansouri, S. A., & Gallear, D. (2016). Is lean service promising? A socio-technical perspective. International Journal of Operations and Production Management, 36(3), 618-642.
- Hair, J., Hult, G., Ringle, C., & Sarstedt, M. (2017). A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM). SAGE Publication.
- Hidayah, N., Hapsari, D. W., Saputra, K. A. K., Dharmawan, N. A. S., & Yadiati, W. (2023). Can Institutional Good Governance and Intellectual Capital Affect University Quality? International Journal of Economics and Management, 17(2), 251-261.
- Holt, H. S. F., Armenakis, A. A., Field, H. S., & Harris, S. G. (2007). Readiness for Organizational Change: The Systematic Development of a Scale. Journal of Applied Behavioral Science, 43(2), 232-255.
- Jarvis, D. S. L. (2014). Regulating higher education: Quality assurance and neo-liberal managerialism in higher education – A critical introduction. Policy and Society, 33, 155-166.
- Jones, G. R. (2013). Organizational theory, design, and change (7th ed.). Pearson.
- Kang, Y., & Liu, R. (2021). Does the merger of universities promote their scientific research performance? Evidence from China. Research Policy, 50, 104098.
- Kusumawijaya, I. K., & Astuti, P. D. (2023). The effect of human capital on innovation: The mediation role of knowledge creation and knowledge sharing in small companies. Knowledge and Performance Management, 7(1), 64-75.
- Lopes, R. B., Freitas, F., & Sousa, I. (2015). Application of Lean Manufacturing Tools in the Food and Beverage Industries. Journal of Technology Management & Innovation, 10(3).
- Maxwell, T. M., & Smyth, R. (2011). Higher degree research supervision: from practice toward theory. Higher Education Research & Development, 30(2), 219-231.
- Mohammad, I. S., & Oduoza, C. F. (2019). Interactions of Lean enablers in Manufacturing SMEs using Interpretive Structural Modelling Approach – a case study of KRI. Procedia Manufacturing, 38, 900-907.
- Naoreen, B., & Adeeb, M. A. (2014). Investigating Academic Research Culture in Public Sector Universities of Pakistan. Procedia - Social and Behavioral Sciences, 116, 3010-3015.
- Ogbeibu, S., & Gaskin, J. (2023). Back from the Future: Mediation and Prediction of Events Uncertainty through Event-Driven Models (EDMs). FIIB Business Review, 12(1), 10-19.
- Ommering, B. W. C., van Blankenstein, F. M., Waaijer, C. J. F., & Dekker, F. W. (2018). Future physician-scientists: could we catch them young? Factors influencing intrinsic and extrinsic motivation for research among first-year medical students. Perspectives on Medical Education, 7(4), 248-255.
- Osborne, S. P., Radnor, Z., & Nasi, G. (2013). A New Theory for Public Service Management? Toward a (Public) Service-Dominant Approach. American Review of Public Administration, 43(2), 135-158.
- Petersen, A. M., Fortunato, S., Pan, R. K., Kaski, K., Penner, O., Rungi, A., Riccaboni A., Stanley, H. E., & Pammolli, F. (2014). Reputation and impact in academic careers. PNAS, 111, 15316-15321.
- Petrusch, A., Roehe Vaccaro, G. L., & Luchese, J. (2018). They teach, but do they apply? An exploratory survey about the use of Lean thinking in Brazilian higher education institutions. International Journal of Lean Six Sigma, 10(3), 743-766.
- Prabowo, H. A., Farida, F., & Adesta, E. Y. T. (2022). The Effect of Lean Waste Reduction Technique to Business Results: a Confirmatory Study. Management and Production Engineering Review, 13(2), 92-101.
- Purushothaman, M. B., Seadon, J., & Moore, D. (2020). Lean tools in a multicultural environment. Journal of Cleaner Production, 265, 121681.
- Radnor, Z. (2010). Transferring lean into government. Journal of Manufacturing Technology Management, 21(3), 411-428.
- Ratter, E., & Nader, S. (2022). The use of lean management tools in production companies with implemented total quality management (TQM). European Research Studies Journal, XXV(3), 357-368.
- Realyvásquez-Vargas, A., Arredondo-Soto, K., Carrillo-Gutiérrez, T., & Ravelom G. (2018). Applying the Plan-Do-Check-Act (PDCA) Cycle to Reduce the Defects in the Manufacturing Industry. A Case Study. Applied Sciences, 8(11), 2181.
- Sanyal, B. C., & Martin, M. (2007). Quality Assurance and The Role of Accreditation: An Overview. Higher Education in The World 2007.
- Scalia, M., Barile, S., Saviano, M., & Farioli, F. (2018). Governance for sustainability: a triple-helix model. Sustainability Science, 13(5), 1235-1244.
- Sharma, M., Kumar, U., & Lalande, L. (2006). Role of University Technology Transfer Offices in University Technology Commercialization: Case Study of the Carleton University Foundry Program. Journal of Services Research, 6, 109-139.
- Silva, S., Sá, J. C., Silva, F. J., Ferreira, L. P., & Santos, G. (2020). Lean green – the importance of integrating environment into lean philosophy – a case study. In Proceedings of the 6th European Lean Educator Conference (pp. 211-219). Springer International Publishing.
- Sonnentag, S., & Frese, M. (2009). Dynamic Performance. In S. W. J. Kozlowski (Ed.), The Oxford Handbook of Industrial Psychology (Vol. 1, pp. 548-575).
- Spear, S., & Bowen, H. K. (1999). Decoding The DNA of The Toyota Production System. Harvard Business Review.
- Sukirno, S. (2020). Dataset of lecturer performance appraisal. Data in Brief, 32, 106161.
- Tyagi, S., Cai, X., Yanga, K., & Chambers, T. (2015). Lean tools and methods to support efficient knowledge creation. International Journal of Information Management, 35(2), 204-214.
- Urban, W. (2015). The Lean Management Maturity Self-Assessment Tool Based on Organizational Culture Diagnosis. Procedia - Social and Behavioral Sciences, 213, 728-733.
- Vlachos, I., & Siachou, E (2018) An empirical investigation of workplace factors affecting lean performance. International Journal of Productivity and Performance Management, 62(2), 278-296.
- Vukadinovic, S., Djapan, M., & Macuzic, I. (2016). Education For Lean & Lean for Education: A Literature Review. International Journal for Quality Research, 11(1), 35-50.
- Waldinger, E. (2010). Quality matters: the expulsion of professors and the consequences for PhD student outcomes in Nazi Germany. Journal of Political Economy, 118(4), 787-831.
- Womack, J. P., & Jones, D. T. (1996). Lean Thinking. New York, NY: Simon and Schuster.
- Worley, J. M., & Doolen, T. L. (2015). Organizational structure, employee problem solving, and lean implementation. International Journal of Lean Six Sigma, 6(1), 39-58.
- Zhang, L., & Chen, X. (2016). Role of lean tools in supporting knowledge creation and performance in lean construction. Procedia Engineering, 145, 1267-1274.
- Zhang, X. (2014). Factors that Motivate Academic Staff to Conduct Research and Influence Research Productivity in Chinese Project 211 Universities (Doctoral Thesis). University of Canberra, Australian Capital Territory, Australia.
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Perceived health risk, online retail ethics, and consumer behavior within online shopping during the COVID-19 pandemic
Yuniarti Fihartini ,
Arief Helmi ,
Meydia Hassan ,
Yevis Marty Oesman
doi: http://dx.doi.org/10.21511/im.17(3).2021.02
Innovative Marketing Volume 17, 2021 Issue #3 pp. 17-29 Views: 4519 Downloads: 1730 TO CITE АНОТАЦІЯThe risk of virus contracting during the COVID-19 pandemic has changed consumer preference for online shopping to meet their daily needs than shopping in brick-and-mortar stores. Online shopping presents a different environment, atmosphere, and experience. The possibility of ethical violations is higher during online than face-to-face transactions. Therefore, this study was conducted to investigate the influence of perceived health risk and customer perception of online retail ethics on consumer online shopping behavior during the COVID-19 pandemic, involving seven variables, namely perceived health risk, security, privacy, non-deception, reliability fulfillment, service recovery, and online shopping behavior. The data were collected through an online survey by employing the purposive sampling technique to a consumer who has shopped online during the COVID-19 pandemic in Indonesia. 315 valid responses were obtained and analyzed through quantitative method using SEM-Amos. The results showed that perceived health risk and four variables of online retail ethics including security, privacy, reliability fulfillment, and service recovery affected online shopping behavior. Meanwhile, non-deception was found to have an insignificant effect. The coefficient value proved perceived health risk to be more dominant in influencing online shopping behavior than the variables of online retail ethics. Thus, consumers pay more concern for their health during online shopping. However, positive consumer perceptions of the behavior of online retail websites in providing services also can encourage consumers to shop online during this pandemic.
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Investigating the impact of workplace bullying on employees’ morale, performance and turnover intentions in five-star Egyptian hotel operations
In today’s competitive business environment, human resources are one of the most critical assets particularly for service-focused organizations. Consequently, employees’ morale has become invaluable for maintaining outstanding organizational performance and retaining employees. One of the most important factors which may affect employees’ satisfaction is workplace bullying from employers and colleagues at large. It is considered a negative and unethical issue which may degrade, humiliate and create a risk to a healthy working environment. Therefore, the main objective of this research is to investigate the extent to which workplace bullying may affect the organizational outcomes of a sample of five-star hotels in Egypt. Two questionnaires were distributed among the subjects of the sample; bell desk staff, kitchen stewards and head departments. The results of this research confirmed that there is a correlation between workplace bullying, employees’ morale and turnover intentions but, showed no correlation between workplace bullying and employees’ work performance.
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Human resource management in promoting innovation and organizational performance
I Gede Riana ,
Gede Suparna ,
I Gusti Made Suwandana ,
Sebastian Kot 
,
Ismi Rajiani
doi: http://dx.doi.org/10.21511/ppm.18(1).2020.10
Problems and Perspectives in Management Volume 18, 2020 Issue #1 pp. 107-118 Views: 3558 Downloads: 851 TO CITE АНОТАЦІЯHuman resource management (HRM) is one of the elements enabling an organization to remain competitive in turbulence conditions. The effective practice of HRM makes competent and innovative employees contributing to the achievement of organizational objectives. This study aims to analyze HRM practices in creating innovation and organizational performance. The questionnaire was used to measure the respondents’ perceptions of variables used by a Likert scale. A survey of 126 manager samples and middle managers at export-oriented short and medium enterprises (SMEs) in Bali, Indonesia, was conducted to test the model. The analysis has shown that the proposed model was proven to be compliant with the research hypotheses. HRM significantly affects organizational performance and innovation, and it was found out that innovation can improve organizational performance. However, in the process of simultaneous testing, it was found out that innovation cannot improve organizational performance. The lack of attention to investments in human resources became one of the barriers to SMEs in creating innovation.
