مدل هوشمندی بازاریابی صنعت خودرو داخلی

نوع مقاله : مقاله علمی پژوهشی

نویسندگان

1 دانشجوی دکتری، گروه مدیریت بازرگانی، دانشگاه پیام نور، تهران، ایران

2 دانشیار، گروه مدیریت اجرایی و MBA، دانشگاه پیام نور، تهران

3 استادیار، گروه مدیریت بازرگانی،دانشگاه پیام نور، تهران، ایران

4 استادیار، گروه مدیریت بازرگانی، دانشگاه پیام نور، تهران، ایران

چکیده

هدف: سازمان برای بقا در بازارهای پویا و متغیر به ابزاری نیاز دارد که با کمک آن بتواند بر چالش‌های محیطی فضای رقابت فائق آید. چنین ابزاری، هوشمندی بازاریابی است. هدف از انجام این تحقیق ارائه یک مدل هوشمندی بازاریابی است که چگونگی تدوین هوشمندی بازاریابی را به صورتی کاربردی و گام به گام تعیین می کند.
روش: در این راستا با مطالعه گسترده ادبیات موضوع به‌خصوص به‌منظور کسب دستیابی به نگاه اسلامی ایرانی، مراجعه به اسناد بالادستی، 47 فاکتور اصلی هوشمندی بازاریابی شناسایی شد و پس از ساختاردهی با ابزار تحلیلی سه‌شاخگی، در قالب پرسش‌نامه‌ای در اختیار خبرگان صنعت خودروی ایران قرار گرفت. با تحلیل آماری داده‌های به‌دست‌آمده از پرسش‌نامه جمع‌آوری‌شده، ده متغیر تأثیرگذار بر هوشمندی بازاریابی شناسایی‌شده، تأیید شدند. سپس متغیرهای شناسایی‌شده، در پرسش‌نامه دوم که با ساختار تکنیک ISM تنظیم شد، وارد شدند. این پرسش‌نامه در اختیار خبرگان صنعت خودروی ایران قرار گرفت و پرسش‌نامه‌ها جمع‌آوری شد.
یافته‌ها: بر مبنای نتایج پرسش‌نامه دوم و با استفاده از تکنیک ISM ، مدل «هوشمندی بازاریابی» طراحی شد.
نتیجه‌گیری: بینشی که این مدل به مدیران ارائه می‌کند، می‌تواند آنها را در تحقق هوشمندی بازاریابی در سازمان یاری دهد. در تحقیقات آتی، می‌بایست به بررسی دلایل و مشکلات اصلی سازمان‌ها در پیاده‌سازی مدل هوشمندی بازاریابی، رد مدل نام‌برده، تحت بررسی قرار دادن مدل هوشمندی بازاریابی و دلیل بررسی نکردن آن مدل در سازمان پرداخت.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Developin a Model for Marketing Intelligence of Internal Automotive Industry

نویسندگان [English]

  • Babak Yavarifar 1
  • Mohammad Mahmoudi Maymand 2
  • Ozhan karimi 3
  • Seyed Mousa khademi 4
1 PhD Candidate, Department of Business Management, Payam-e- Noor University, Tehran, Iran.
2 Associate Prof., Department of Business Administration & MBA, Payam- e- Noor University, Tehran, Iran.
3 Assistant Prof., Department of Business Management, Payam-e- Noor University, Tehran, Iran.
4 Assistant Prof., Department of Business Management, Payam-e- Noor University, Tehran, Iran.
چکیده [English]

Objective
Inter-organizational intelligence is an effective way for organizations to adapt to the external environment, overcome the possible threats and seize opportunities. And since receiving information from the outside of the business environment affects the competitive position and effectiveness of the organization's marketing policies, it is important to pay attention to the kind of information needed for the organizations and the fact that how much they use intelligence in their strategic decisions. Considering the influence and background of Iran's automotive industry with an eight-decade history in the country and with various ups and downs as well as a special place in terms of cross-sectoral links in the Iran economy, we intended to identify the key factors affecting marketing intelligence based on the experts’ opinions. And then, we aim to present a conceptual model, using ISM technique, to identify the sequences and relevance of these factors.
 
Methodology
Based on the nature of the subject and the objectives, the present research is a survey. At first, through reviewing the literature and interviewing experts, marketing intelligence factors were identified and then a questionnaire was designed to determine the importance of each factor. The statistical population of the present study is the Iranian automotive industry including the experts, managers and assistants of strategy, marketing and sales units. Participants were selected based on stratified random sampling proportional to the number of employees in each corporate unit. Confirmatory factor analysis was used to extract the factors (from the first questionnaire) and also to determine the structural validity and suitability of the model. LISREL and SPSS software were used for data analysis. ISM calculations were performed manually to obtain the relationship and sequence of variables from the second questionnaire.
 
Findings
The results of the ISM indicated that the ten approved marketing intelligence factors fall into six levels. The last level in the ISM represents a factor that performs as the cornerstone of the model and underlies the factors of previous levels. The first level in the ISM represents the factors highlighting the ultimate outcomes of the model. In other words, these are the factors that are obtained through other contributors.
 
Conclusion
Within the obtained model in this study, the monitoring of online communications, governmental information sources and information vendors are at the first level. While, at the bottom of the model is the country's priority factor which is the cornerstone of marketing intelligence in an organization, and the marketing should start emphasizing on this factor. Organization’s directional factors are located at the fourth level which is affected by the intelligent marketing enablers (within the fifth and sixth levels). That is, this factor palys a mediating role in marketing intelligence.

کلیدواژه‌ها [English]

  • Marketing intelligence
  • Structural interpretive modeling
  • Three-branch model
آزاد، شهرام؛ شریفی، کیومرث (1390). بررسی وضعیت سیستم‌های اطلاعات بازاریابی شرکت‌های متوسط و بزرگ صنایع غذایی.  مدیریت بازرگانی، 4(13)، 1-24.
اژدری، علی اصغر؛ شجاعی، سعید (1394). آسیب‌شناسی صنعت خودروی کشور و ارائه راهکارهای برون‌رفت از چالش‌های موجود در راستای سیاست‌های کلی اقتصاد مقاومتی. قابل دسترس در سایت مرکز پژوهش‌های مجلس شورای اسلامی.
بیک زاد، جعفر؛ اسکندری، کریم (1388). هوش رقابتی مدیران و توسعه صنایع کوچک. کار و جامعه، (113 و 114)، 14-20.
پیرایش، رضا؛ علی پور، وحیده (1391). بررسی رابطه‎ بین هوش رقابتی و اثربخشی استراتژی‎های بازاریابی در بین بانک‎های دولتی و خصوصی استان زنجان. مدیریت بازرگانی،  4(12)، 1-18.
حبیبی، آرش؛ عدن‌ور، مریم (1396). مدل‌یابی معادلات ساختاری (چاپ اول). تهران: انتشارات جهاد دانشگاهی.
دلاور، علی (1385). مبانی نظری و عملی پژوهش در علوم انسانی و اجتماعی. تهران:  انتشارات رشد.
دلاور، علی (1396). احتمالات و آمار کاربردی در روان‌شناسی و علوم تربیتی. تهران: انتشارات رشد.
سرمد، زهره؛ بازرگان، عباس؛ حجازی، الهه (1384). روش‌های تحقیق در علوم رفتاری. تهران: انتشارات آگاه.
کرلینجر، فرد (1382). مبانی پژوهش در علوم رفتاری. (پاشا شریفی، مترجم). تهران:  انتشارات آوای نور.
گلستانی، صادق (1386). نقد نگاه سکولاریستی به اسلام. مطالعات انقلاب اسلامی، (8)، 169- 181.
قاضی طباطبائی، محمود (1377). ارزیابی اعتبار سازهای: نخستین گام ضرور در مطالعات بین فرهنگی (مورد: پرسش‎نامه گیبسون و دمبو). نشریه نامه علوم اجتماعی دانشگاه تبریز، (12)، 135 -107.
هومن، حیدرعلی (1385). مدل‌یابی معادلات ساختاری با کاربرد نرم‌افزار لیزرل. تهران: انتشارات سمت.
هومن، حیدر علی؛ عسگری، علی (1384). تحلیل عاملی: دشواری‎ها و تنگناهای آن. مجله روانشناسی و علوم تربیتی، 35(2)، 1-20.
وظیفه دوست، حسین؛ قاسمی، فاطمه (1387). هوشمندی رقابتی رویکردها و کاربردها. مجله تدبیر، 19(197).
 
References
Adidam, Ph., Gajre, S. & Kejriwal, Sh. (2009). Cross–cultural competitive instelligence strategies. Journal of Marketing Intelligence and Planning, (5), 666-680.
Agarwal, A., Shankar, R., Tiwari, M.K. (2007). Modeling agility of supply chain. Industrial Marketing Management, 36, 443-445.
Ahire, S.L., Golhar, D.Y., Waller, M.A. (1996). Development and validation of TQM implementation constructs. Decision Sciences, 27(1), 23–56.
Ajdari, A.A., & Shojaee, S. (2015). Pathology of the Automotive Industry of the Country and Providing Solutions to Overcoming Challenges to the General Policies of Resistance Economics. Available on the web site of the Parliament Research Center. (in Persian)
Auxilidora, M., Melo, N. & Medeiros, D. (2007). A model for analyzing the competitive strategy of health plan in sures a system of competitive intelligence. The TQM Magazine, 3, 206-216.
Azad, Sh., & Sharifi, K. (2012). Investigating the status of marketing information systems of middle and large food companies. Journal of Business Management, 4(13), 1-24.
(in Persian)
Beakzad, J., & Eskandari, K. (2009). Competitive Intelligence of Managers and Development of Small Industries. Labor and Society, (113 and 114), 14-20.
Bolanos, R., Fontela, E., Nenclares, A., Paster, P. (2005). Using interpretive structural modeling in strategic decision making groups. Management Decision, 43(6), 877−895.
Boon, W., & Edler J. (2018). Demand, Challenges and Innovation. Making Sense of New Trends in Innovation Policy. Science and Public Policy, 45(4), 435–447.
Borrás, S., & Edquist, C. (2017). Innovations – A Systems Activities Approach. In: Borrás S., Edquist C. (eds) Holistic Innovation Policy: Theoretical Foundations, Policy Problems and Instrument Choices. Oxford: Oxford University Press.
Boyer, K.K., Pagell, M. (2000). Measurement issues in empirical research: Improving measures of operations strategy and advanced manufacturing technology. Journal of Operations Management, 18(3), 361–374.
Churchill, G. A. (1979). A paradigm for developing better measures of marketing constructs. Journal of Marketing Research, 16(1), 64–73.
Chung, W., Tseng, T. (2012). Discovering business intelligence from online product reviews: A rule induction framework. Expert Systems with Applications, 39, 11870-11879.
Cito, M. C., Leung E., Paolacci, G., & Puntoni, S. (2018). Dematerialization and Identity-based Consumer Behavior. Working paper.
Crollinger, F. (2003). The Basics of Behavioral Sciences Research. (Pasha Sharifi, Translat). Tehran, Avaya Noor Publications. (in Persian)
Delawar, A. (2006). Theoretical and practical bases for research in humanities and social sciences, Tehran, Growth Publishing. (in Persian)
Delawar, A. (2016). Probability and Applied Statistics in Psychology and Educational Sciences. Growth Publishing. (in Persian)
Frenken, K. (2017). A Complexity-Theoretic Perspective on Innovation Policy. Complexity, Governement & Networks, 35–47.
Frishammar, J. (2002). Characteristics in Information Processing Approaches. International Journal of Information Management, 22 (2), 143-156.
Fuld, L. (1995). The New Competitor Intelligence, Wiley, New York.
Ghazi Tabatabai, M. (1998). Evaluating Instrumental Validation: An Essential Step in Intercultural Studies (Gibson and Dembo Questionnaire). Journal of Social Sciences, (12), 135-107. (in Persian)
Goetzmann, W. N., Kim, D., Shiller, R.J. (2016). Crash Beliefs from Investor Surveys. National Bureau of Economic Research. Working Paper, No. 22143.
Golestani, S. (2007). Criticism of the secularist view of Islam. Proceedings of the Islamic Revolution, 8, 169-181.
Habibi, A., & Adanvar, M. (2017). Structural Equilibrium Modeling Book. (1 ed). Jahad University Press. (in Persian)
Hooman, H. (2006). Structural Equation Modeling Using LaserL Software. Tehran, Sadegh.
(in Persian)
Huang, J.J., Tzeng, G., Ong, Ch. (2005). Multidimensional data in multidimensional scaling using the analytic network process. Pattern Recognition Letters, 26, 755–767.
Kahaner, L. (1996). Competitive Intelligence: How to Gather, Analyze, and Use Information to Move your Business to the Top. Simon & Schuster, New York.
Kaiser, H. F., Cerrny, B.A. (1997). A study of a measure of sampling adequacy for factor-analytic correlation matrices. Multivariate Behavioral Research, 12, 43-47.
Kaynak, H. (2003). The relationship between total quality management practices and their effects on firm performance. Journal of operations management, 21(4), 405-435.
Kim, T.N. (2015). Korea auto industry achievements & challenges, Korea automobile manufacturers association. Available in: http://kama.or.kr/eng/PS/pdf/Total2014.pdf.
Li, D., O’Brien, C. (1999). Integrated decisions modeling of supply chain efficiency. International Journal of Production Economics, 59, 174-159.
Lin, C., Wu, J. C. & Yen, D. C. (2012). Exploring barriers to knowledge flow at different knowledge management maturity stages. Information  &Management, 49(1), 10-23.
Mandal, A., Deshmukh, S.G. (1994). Vendor selection using interpretive structural modeling (ISM). International Journal of Operation & Production Management, 14(6), 52-59.
McGonagle, J.J. & Vella, C.M (1997). The Intelligence Age of Competitive Intelligence, CT: Greenwood Publishing Group, Inc, Westport.
Nunnally, J.C. & Bernstein, I.H. (1994). Psychometric Theory. 3rd ed. McGraw-Hill Inc., New York.
Patterson, L. (2017). Markets Calling: Intelligence Gathering at the Bank of Canada. Speech at the CFA Society Calgary, Calgary, Alberta, June 28.
Pichette, L., & Robitaille, M.N. (2017). Assessing the Business Outlook Survey Indicator Using Real-Time Data. Bank of Canada Staff Discussion, Paper No. 2017-5.
Pichnorak, S. & Vouchneng, S. (2016). The Roles of Export-led Policies in Developing Automobile Industry in South Korea. available at: www.academia.edu/3727668/Roles _of_export.
Pinkerton, R. L. (1969). How to develop a marketing intelligence system, Industrial Marketing (series of five articles) April, May, June, July and August.
Piraiesh, R., Alipour, V. (2012). Investigating the Relationship between Competitive Intelligence and the Effectiveness of Marketing Strategies between Public and Private Banks in Zanjan Province. Business Management, 4 (12), 1-18. (in Persian)
Porter, M. E. (1985). Competitive Advantage: Creating and Sustaining Superior Performance, Free Press, New York.
Porter, M.E (1987). Competitive strategy, Free Press, New York.
Prescott, J. E. (1989). Advances in Competitive Intelligence. Society of Competitive Intelligence Professionals, New York.
Qiu, T. (2008). Scanning for competitive intelligence: A managerial perspective. European Journal of Marketing, 42(7-8), 814–835.
Rogge K. S., Reichardt K. (2016). Policy Mixes for Sustainability Transitions: An Extended Concept and Framework for Analysis. Research Policy, 45(8), 1620–35.
Sarmed, Z., Bazargan, A., Hejazi, E. (2005). Research Methods in Behavioral Sciences, Tehran, Ajagh Publications. (in Persian)
Shleifer, A., & Jenayolly, R. (2016). A survey of corporate governance. Journal of Finance, 52, 737-775.
Tari, J.J., Molina, J.F, Castejon, J.L. (2007). The relationship between quality management practices and their effects on quality outcomes. European Journal of Operational Research, 183, 483–501.
Vazifedoost, H., Qasemi, F. (2008). Competitive Intelligence of Approaches and Applications. Tadbir Magazine, 19 (197), No. 197. (in Persian)
Venkatraman, N. (1989). The concept of fit in strategy research: Toward verbal and statistical correspondence. Academy of Management Review, 3, 423- 444.
Wesseling, J. H., Van der Vooren, A. (2017). Lock-in of Mature Innovation Systems: The Transformation toward Clean Concrete in the Netherlands. Journal of Cleaner Production, 155, 114–24.
Yap, C. S. & Rashid, M. A. (2011). Acquisition and strategic use of competitive Intelligence. Malaysian Journal of Library & Information Science, 16(1), 125-136.
Ghazanfari, M., Jafari, M., Rouhani, S. (2011). A tool to evaluate the business intelligence of enterprise systems. Scientia Iranica, 18 (6), 1579–1590.
Zhang, X., Majid, S. & Foo, S. (2010). Environment scanning: An application of information literacy skills at the workplace. Journal of Information Science, 36(6), 719- 732.