Presenting a Model of Improving Productivity in Wood Industry: a Commercialization Approach toward University Knowledge

Subject Areas : Industrial Management

Nasrin Khodabakhshi Hafashjani ^{1 *}

1 - Assistant Professor of Management Department, Faculty of Humanities, Khalkhal Azad University, Khalkhal, Iran.

Received: 2022-11-24 Accepted : 2023-02-08 Published : 2023-12-12

Keywords: Productivity, Commercialization, Idea, structural-interpretive,

Abstract :

Knowledge transfer between university and industry is an important driver in innovation and economic growth. The purpose of this study was to design a model for improving productivity in wood industry focusing on the commercialization of university knowledge and ideas. This research was developmental-applicative, a mixed method (qualitative-quantitative) study with a combined exploratory-sequential design. The target community of the research was experts who were aware of the research topic. In order to conduct in-depth interviews and collect qualitative data, from the targeted snowball technique to the theoretical saturation stage, 17 people were selected as a sample and in order to complete the researcher-made questionnaires in the quantitative section, a sample of five people was suggested. The validity of the qualitative data of the research was confirmed through continuous observation and review by a colleague and the reliability of these data was estimated to be 89% using the two-coder index method. The validity of the quantitative data was found to be 80% by using the Lawshe content validity ratio and their reliability was 86% using the Cronbach’s alpha coefficient.  Conducting the thematic analysis method based on the model of Braun and Clark (2006), the effective indicators of improving productivity with a commercialization approach toward university knowledge and ideas were identified and then modeling was done using structural-interpretive analysis (ISM). Based on the results of the research, 114 primary concepts were identified including 20 sub-themes and 13 main themes. These indicators were at six levels of the structural-interpretive model consisting of the index of strategic plans at the sixth level, the structure and support management at the fifth level, the development of interaction at the fourth level, the improvement of the educational system, the development of infrastructure and the personal characteristics at the third level, the indicators of modeling, industrialization, motivation, human resources, and attracting the private sector at the second level, and the marketing index was at the first level. Therefore, managers and policy makers need to understand the nature and relationships among the identified indicators in wood industry and apply the necessary measures in this field in order to improve productivity in industries with a commercializing approach toward university knowledge and ideas.

Key Words: productivity, commercialization, university knowledge and idea, structural-interpretive

1. Introduction

In today's view, universities have more responsibility in transforming their ideas and research achievements into factors that provide economic growth, wealth in society and public-welfare, and should make efforts to transfer and apply knowledge into various sectors of industry, society and economy. One of the important mechanisms for practical access to university knowledge and ideas in order to improve productivity in industries is the commercialization of university ideas. Therefore, this research seeks to answer the following basic question:

What are the indicators that affect the improvement of productivity in the field of wood industry and their cause-effect relationships based on the structural-interpretive model?

2. Literature Review

Productivity refers to the effective and efficient use of data to achieve results. Through increasing the productivity of the existing inputs in the economy, more added value is created and as a result, more income is provided and distributed among the production factors. Productivity is a comprehensive and general concept, which is one of the most basic ways to achieve more production, and hence, it is considered a necessity to provide welfare and promote the well-being of people in societies, which is always the focus of economists, politicians and managers in different countries (Ammer, 2019). Therefore, one of the main drivers of economic growth and the main factor in improving productivity in various industries is the use of university knowledge and ideas (Fini & et al, 2018). Commercialization refers to a set of activities carried out in order to transform knowledge and new ideas into products, processes and services in response to market opportunities (Gibson & et al, 2019).

3. Methodology

In terms of nature, this study is of a mixed type (qualitative-quantitative). The qualitative phase was conducted to identify the factors affecting the productivity improvement indicators of the wood industry with a commercialization approach toward university ideas, according to the thematic analysis based on the Braun and Clark method and the quantitative part of the research was drawn using the structural-interpretive modeling (ISM). The statistical community of the research included some university faculty members who were experts in the field of productivity and commercialization, managers and members of the academic Jihad Science and Technology Park active in the field of commercialization and technology, and people working in the wood industry, familiar with the subject of the research. For sampling in the qualitative part, non-random sampling method with a targeted approach and chain reference type (snowball) and the theoretical saturation technique (17 people) were used, and in the quantitative part, five people were suggested as the sample. The qualitative data were collected through in-depth interviews with experts and analyzed using the six-step method of Braun and Clark (2006). Maxqda₁₀ software was used to identify the themes. To collect the quantitative data, the factors identified in the matrix table were prepared in the form of a questionnaire and distributed to the research sample. In order to analyze the data, structural-interpretive modeling (ISM) steps were performed using Matalab_2016a software. The validity of the qualitative data was calculated by the method of review, done by a colleague and the participants, and their reliability was calculated through the two-coder index (89%). The validity of the quantitative data was estimated through the Lawshe content validity ratio (80%) and their reliability through Cronbach's alpha (86%).

4. Results

In the qualitative part of the research, after analyzing and examining the themes of the interviews, 114 initial concepts were extracted. The initial concepts were categorized into 20 sub-themes in the next stage and these themes were categorized into 13 main themes in the final analysis. In the quantitative part of the research, the structural-interpretive model of the research was also presented in six levels. The "marketing" index was placed at the first level, so that this index was at the highest position in the hierarchy of the structural-interpretive model of improving the productivity of wood industries with the commercialization approach of university ideas, which means that it does not influence the indicators, but is influenced by all of them, the index of "strategic programs" at the sixth level affects other indicators of improving productivity through the commercialization of ideas. Moreover, the identified indicators of improving the productivity of the wood industry were placed in three dependent, connected and independent categories, none of which was included in the autonomous group. It shows the importance of the identified indicators. Also, the indicators of individual characteristics, infrastructure development, attraction of the private sector, human resources, development of interaction, improvement of the educational system, industrialization, and modeling were in the connected category, which were identified as key indicators that any change in one of them would cause change in the other indicators

5. Discussion

The entry of universities into the field of business and marketing, followed by paying attention to market requirements and customer standards, in itself, is the result of some opportunities and positive consequences, which at least, help the self-governance of the university and ideally, may result in improving the living standards (safety and security), quality of life, wealth production and economic growth. On the other hand, industries also need academic knowledge and ideas to innovate and improve their activities, have product diversity, improve quality and productivity, make economic savings, achieve customer orientation, maintain competitive advantage, train and improve employees and generally develop in different fields.

As indicated by the present research model and the identified indicators, based on the effectiveness and susceptibility of the indicators, it is necessary for the policy makers of the Ministry of Science and universities to grow and increase university ideas in various fields and pursue commercialization. They have to take fundamental steps to develop standards and regulations in this field and pay special attention to the promotion and institutionalization of this matter. In addition, managers and investors in various industries such as the wood industry, in order to improve the level of productivity, maintain competitive advantage, achieve goals and continue the survival and success of their production units, should pay special attention to university ideas and research in line with their commercialization and provide the necessary goods and services in accordance with the needs of their customers.

 

 

 

 

References:

Ammer, C. (2019). Diversity and forest productivity in a changing climate. New phytologist, 221(1), 50-66. do:10.1111/nph.15263
Bahmani, A., Rafighi, A., Vali, M., & Salari, A. (2012). Identification and Evaluation of Oncoming Changes of Wood and Paper Industries of the Country. Iranian Journal of Wood and Paper Industries, 2(2), 27-38. [In Persian] dor:20.1001.1.20089066.1390.2.2.3.6
Bakhtiar, A., Aslani, A., & Hosseini, S. M. (2020). Challenges of diffusion and commercialization of bioenergy in developing countries. Renewable energy, 145, 1780-1798. doi:10.1016/j.renene.2019.06.126
BayatKashkyli, A., Mehmandoost, M. (2017). The study of production, employment and trade in wood industry of Iran. Journal of Wood and Forest Science and Technology, 24(3), 143-159. [In Persian] doi:10.22069/JWFST.2017.12663.1658
Cao, X., & Hansen, E. N. (2006). Innovation in China's furniture industry. Forest Products Journal, 46(11/12):33-42. http://hdl.handle.net/1957/19878
Carvalho, T., & Diogo, S. (2021). Time and Academic Multitasking–Unbounded Relation Between Professional and Personal Time. In Inquiring into Academic Timescapes (pp. 137-155). Emerald Publishing Limited. doi:10.1108/978-1-78973-911-420211013
Diep, N. A., Cocquyt, C., Zhu, C., Vanwing, T., & De Greef, M. (2017). Effects of core self-evaluation and online interaction quality on adults' learning performance and bonding and bridging social capital. Internet and Higher Education, 34, 41-55. doi:10.1016/j.iheduc.2017.05.002
Eriksson, L., & Kjeang, A. (2021). Local organization for promoting energy efficiency—reform of local energy advice service in Sweden. Energy Efficiency, 14(1), 1-16. doi:10.1007/s12053-020-09923.
Entesar foomani, G. (2015). Relationship between Job Motivation, Job Involvement and Organizational Commitment of Teachers and Managers΄ Productivity in Education Administration of Zanjan. The Journal of Productivity Management, 9(1(32)), 171-190. [In Persian] dor:20.1001.1.27169979.1394.9.1.8.1
Falahpuor, H., Pourhossini, E., Araban, S. (2022). Identifying the Factors Affecting the Productivity of Education Managers in Lorestan Province. The Journal of Modern Thoughts in Education, 17(4), 17-32. [In Persian] dor:20.1001.1.2821059.1401.17.4.2.3
Fini, R., Rasmussen, E., Siegel, D., & Wiklund, J. (2018). Rethinking the commercialization of public science: From entrepreneurial outcomes to societal impacts. Academy of Management Perspectives, 32(1), 4-20. doi:10.5465/amp.2017.0206
Garagozlo, A. (2011). Investigating the role of research and development (R&T) on the productivity of high-tech industries in Iran, Master of thesis, Faculty of Economics and Accounting, Tehran Central Branch Azad University. [In Persian]
García-Buades, M. E., Peiró, J. M., Montañez-Juan, M. I., Kozusznik, M. W., & Ortiz-Bonnín, S. (2020). Happy-productive teams and work units: A systematic review of the ‘happy-productive worker thesis’. International journal of environmental research and public health, 17(1), 69. doi.:10.3390/ijerph17010069
Gibson, E., Daim, T. U., & Dabic, M. (2019). Evaluating university industry collaborative research. Technological Forecasting and Social Change, 146, 181-202. doi:10.1016/j.techfore.2019.05.014
Hashemi, A., & Ghasemi, Y. (2020). Doing a Research by Thematic Analysis: A Practical, Step-by-Step Guide for Learning and Teaching (Case Study: Music usage of M.A. Students at Ilam University), Ilam Culcure, 20(64.65), 7-33.
Hooman,. HA. (2017). Research Methology in Behavioral Sciences (research foundations), 9st Edition, Organization of studying and compiling university books in Islamic and human sciences, 1-524. [In Persian]
Heinecke, S. (2018). On the route towards renewal? The Polish Academy of Sciences in post-socialist context. Science and Public Policy, 45(2), 246-256. https://doi.org/10.1093/scipol/scx063
Iran's 1404 perspective .(2002). 20-Year Perspective Document for Iran. [In Persian]
Imani, MN., & Eyvazi, E. (2018). The strategy of improving educational quality in Iran's Islamic higher education system, Strategy Journal, 27(88), 83 – 97. [In Persian] dor:20.1001.1.10283102.1397.27.3.4.2
Jahed H, Arasteh H.(2013) External organizational factors influencing commercialization of research results. Quarterly Journal of Research and Planning in Higher Education; 19 (1) :45-68. [In Persian]
Jones, H. M., Chen, Y., Gibson, C., Heimbach, T., Parrott, N., Peters, S. A., ... & Hall, S. D. (2015). Physiologically based pharmacokinetic modeling in drug discovery and development: a pharmaceutical industry perspective. Clinical Pharmacology & Therapeutics, 97(3), 247-262. doi:10.1002/cpt.37
Kauff, J. F. (2019). Supporting Employees and Maximizing Profit: The Case for Workforce Development Focused on Self-Regulation. Policy & Practice, 3, 16. doi:10.1108/S0742-730120180000036007
Khastar, H. (2009). A Method for Calculating Coding Reliability in Qualitative Research Interviews. Methodology of Social Sciences and Humanities, 15(58), 161-174.
Li, N., Niu, X., Chen, Q., & Zhou, H. (2020). Towards commercialization: The operational stability of perovskite solar cells. Chemical Society Reviews, 49(22), 8235-8286. doi:10.1039/D0CS00573H
Movahhedi, M. M., & Rezaee Nosrati, V. (2010). Using Condition Monitoring (CM) for Access to Efficiency Improvement in Industry Case Study: Mazandaran Wood and Paper Industries. The Journal of Productivity Management, 4(1 (12)), 49-74. [In Persian] dor:20.1001.1.27169979.1389.4.1.3.1
Narimani, AR,. & ؛ Vaezi, R. (2017). Identify factors to the commercialization of research in Knowledge of public administration, Journal of public administration, 2(9), 235 – 262. [In Persian] doi:10.22059/JIPA.2017.236485.2047
Pishan, S., & Ghafrani, M. (2021). Manpower training and productivity in Iran's wood industry factories, 1st national conference of Islam and science education, Shahid Rajaei University. [In Persian]
Productivity report (2018). Analytical report on the state of productivity of the country's macroeconomics. [In Persian]
Productivity (2021). The document on improving the productivity of Cabinet of Iran the industrial. [In Persian]
Pinto, E. B., & Fernandes, G. (2021). Collaborative R&D the key cooperation domain for university-industry partnerships sustainability–position paper. Procedia Computer Science, 181, 102-109. doi:10.1016/j.procs.2021.01.109
Rahmati, R., & Ranjbar, M. (2016). Explaining the Role of Strategic Planning in Future Defense Technology Development. Military Science and Tactics, 12(36), 141-163. [In Persian]
Ravi, V., Shankar, R., & Tiwari, M. K. (2005). Productivity improvement of a computer. International Journal of Productivity and Performance Management, 54(4), 239-255. doi:10.1108/17410400510593802
Salamati, T., Vaezi, E., Memarpour, M., & Rajabzadeh, A. (2016). Commercialization Model Design and Presentation of Proposed Algorithm of Commercialization for the Higher Education. Knowledge Retrieval and Semantic Systems, 3(8), 61-80. doi:10.22054/jks.2017.22386.1134
Schwab, K., & Sala-i-Martín, X. (2016, April). The global competitiveness report 2013–2014: Full data edition. World Economic Forum, 1-569.
Shakeel, S. R., Takala, J., & Zhu, L. D. (2017). Commercialization of renewable energy technologies: A ladder building approach. Renewable and Sustainable Energy Reviews, 78, 855-867. doi: 10.1016/j.rser.2017.05.005
Sofi Majidpor, M. (2017). The growth of total productivity of production factors, technological progress, efficiency changes: empirical evidence from Iran's manufacturing industries, Ph.D. Thesis, Faculty of Economic and Social Sciences, Bu Ali Sina University. [In Persian]
Soti, A., Shankar, R., & Kaushal, O. P. (2010). Modeling the enablers of Six Sigma using interpreting structural modeling. Journal of Modelling in Management., 3(9): 897-878. doi:10.1108/17465661011060989
Tabatabaee A, Hasani P, Mortazavi H, Tabatabaeichehr M. (2013) Strategies to enhance rigor in qualitative research. Journal of Khorasan University of Medical Sciences, 5 (3) :663-670. 10.29252/jnkums.5.3.663
Taghizadeh, H., & Shokri, A. (2015). Relationship among the dimensions of knowledge management from the viewpoint of social capital based on interpretive structural modelling. Journal of Information & Knowledge Management, 5(19), 23-42. Doi:10.1142/S0219649215500240
Tien, N. H., Jose, R. J. S., Ullah, S. E., & Sadiq, M. (2021). Development of Human Resource Management Activities in Vietnamese Private Companies. Turkish Journal of Computer and Mathematics Education, 12(14), 4391-4401. doi:10.17762/turcomat.v12i12.8213
Upadhyayula, V. K., Gadhamshetty, V., Shanmugam, K., Souihi, N., & Tysklind, M. (2018). Advancing game changing academic research concepts to commercialization: A Life Cycle Assessment (LCA) based sustainability framework for making informed decisions in Technology Valley of Death (TVD). Resources, Conservation and Recycling, 133, 404-416. doi:10.1016/j.resconrec.2017.12.029
Verger, A., Fontdevila, C., & Zancajo, A. (2016). The privatization of education: A political economy of global education reform. Teachers College Press, 1-257.
Yaqoob, S., Riaz, M., Shabbir, A., Zia-Ul-Haq, M., Alwakeel, S. S., & Bin-Jumah, M. (2021). Commercialization and Marketing Potential of Carotenoids. In Carotenoids: Structure and Function in the Human Body (pp. 799-826). Springer, Cham. doi:10.1007/978-3-030-46459-2_27
Yazdani, AM., & Rezaei, A, & Rezaei, S. (2009). Developing the productivity of industries with appropriate policy in energy consumption, a case study: Mazandaran of wood and paper industries. 7st National Energy Conference. [In Persian]
Zolfaghari, A., Zand hessami, H., Akbari, M., & Amin esmaili, H. (2020). Drivers and Obstacles of Technology Commercialization. Innovation Management in Defensive Organizations, 3(3), 51-74. [In Persian] doi:10.22034/QJIMDO.2020.222284.1283