Document Type : Original Article
Authors
1
Department of Business Administration, Payam Noor University, Tehran, Iran.
2
Professor of the Department of Management, Economics and Progress Engineering, Iran University of Science and Technology (IUST), Tehran, Iran.
3
Department of Business Administration, Payam-e Nour University, Tehran, Iran.
4
Assistant Professor, Department of Business Administration, Payame Noor University, Tehran, Iran.
Abstract
This study was carried out to provide a structure of the driving forces that form the strategic alliance in the Inlaid Furniture Industry. This study is a mixed, developmental, applied, and cross-sectional design. Its data collection method was field and its tools were interviews and questionnaires, its philosophical position was interpretive in the qualitative part and positivist in the quantitative part. In the qualitative design, 20 experts were selected in a targeted and snowball method, and 10 people were selected in the quantitative part. The validity and reliability of both tools were evaluated and confirmed in both qualitative and quantitative sections. To analyze the data, the thematic analysis method was used in the qualitative part and the comprehensive structural interpretive modeling method was used in the quantitative part. The drivers of forming a strategic alliance are macro and environmental, industrial, alliance-related, company-related, and marketing mix drivers. The evidence obtained from the Total structural interpretative modeling method showed that the developed conceptual structure has four levels, the first level of which consists of drivers related to the marketing mix, the second level of drivers related to the company and alliance, the third level of those drivers related to Industry and its fourth level are macro and environmental drivers. The results of this study led to the recognition of the drivers of the formation of strategic alliances in the inlaid furniture industry of Malayer City. The drivers identified were placed in four levels and the most effective were macro and environmental drivers.
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