مجله مدیریت تولید و عملیات
سال چهاردهم شماره 4 (پیاپی 35، Winter 2024)

The growth and development of defence industries are essential to improve deterrence and national security. One way to develop such industries is to acquire technology-based firms that, in addition to improving the ability to manufacture new products, can help them meet their operational and strategic goals. Since the valuation of such firms is considered one of the complexities of acquisition, this paper aims to propose a model for their valuation according to the ecosystem of defence industries.

Design/methodology/approach: 

To create the model, first the literature in this field has been investigated. Also, the comments and proposals of senior managers, technical designers and experts, economic and financial specialists, and R&D experts in the defence industries have been surveyed and then, the valuation criteria for technology-based firms have been identified using the fuzzy screening technique. Next, by using the fuzzy Analytic Hierarchy Process (AHP), the relative importance coefficients for components, criteria, and subcriteria have been determined, and the valuation model has been developed. Finally, the function of estimating the value of technology-based firms that can be acquired in the Department of Defense (DOD) has been formulated. The study was carried out at the end of 2022 in DOD strategic organizations.

Since knowledge and intellectual properties are the most significant pillars and competitive advantages of technology-based firms, the results showed that the “intangible assets” criterion is the most significant one for the valuation of firms by a weight of 0.449. Following the criterion are the tangible assets, and the major risks with a weight of 0.351, and 0.20, respectively. In this study, the strategic role and importance of technology-based firms for the defence industries, their synergy with these industries, the protection requirements, as well as the stability and durability of the technology-based firms in the condition of disruption were introduced as specific criteria in the valuation model for the firms. Also, the result of the sensitivity analysis indicated that the ranking of options is the most sensitive subject to changes in the importance and weight of intangible assets and the main risk.

Research limitations/implications:

 One of the limitations of the research is that this study was not conducted in a specific defence industry such as electronics and radar, energy-rich materials, chemical, air, or marine industries, and was comprehensively planned in all industries. Since tangible, and intangible assets or even risks may be different in each of such industries, this issue leads to the cautious use of the model in each of these specialized areas. Another limitation was the research statistical population, which only included university professors, senior managers and financial managers of defence industries. Although using the opinions of capital market valuation experts venture capitalists and expert valuation experts of the country's innovation and knowledge ecosystem for further validation of the model and criteria statistics and to specify the specific conditions of valuation in the defence environment, seemed useful, there were limitations in their assessment.

Originality/value: 

Proposing a hybrid model including tangible and intangible assets and considering risks, and also considering the key criteria of the defence sector such as strategic importance, synergy stability and durability of firms, as well as providing functions for estimating the value of technology- base firms that can be acquired in DOD are considered as the two of the most important aspects of contributions and innovations of this research. The current model provides a systematic and scientific plan for defence industry managers and experts who can use it in the valuation of companies that can be acquired in the defence industry and be sure that their interests are taken into account.

This study aims to propose an approach for analyzing the supplier-producer relationship quality.

Design/methodology/approach:

 A questionnaire has been compiled and distributed to two transportation and concrete producer companies. The relationship quality by its constituent dimensions has been investigated with the aid of gap analysis and quadrant analysis.

Findings indicated that the most of relationship quality dimensions have been located in the main strength point and only three dimensions of dependency and power, relationship-specific adaptations and investments, and cooperation and coordination have been addressed as critical and required improvement.

Practical implications:

 This article extends the application of quality management tools and techniques to a particular area of supply chain quality management, i.e., supplier-producer relationship quality management. The proposed approach enables suppliers and producers to evaluate their relationship quality faster and recognize the dimensions that are critical and need improvement.

Research limitations/implications:

 the comprehensive list of dimensions together with the proposed integrative approach seems effective in facilitating the analysis of the relationship quality between producer and supplier. By the use of gap analysis and quadrant analysis, parties can evaluate the relationship quality faster and recognize the dimensions that need improvement and are critical in relationship quality.

Originality/value: 

The proposed approach of the integration of gap and quadrant analysis is unique compared to the existing literature. Also, the dimensions of the relationship quality have been considered, comprehensively.

Sometimes the performance of a process is better analyzed by panel data rather than measurements on only a time series. When a change manifests itself in the cross-section(s) of panel data, detection of the real-time change corresponding to the panel data leads practitioners to identify the responsible factor(s) that affected the distribution of the panel. This invaluable time analysis is referred to as the change point. This paper proposes a new effective method to identify the change point of the panel data case.

Design/methodology/approach:

 Considering cross-sectional time series, the identification of the change point of panel data has been evaluated. Two real cases have been studied to analyze the performance of the proposed method.

The comparative numerical performance analysis of different simulated cases indicates that the proposed method is more effective compared to the methods proposed in the literature.

Practical implications:

 The investigation of two real case studies in this paper addresses that the proposed method allows practitioners to use the proposed applied approach for analyzing different real panel cases.

Implementing Industry 4.0 in manufacturing organizations can help establish predictive maintenance, fostering sustainability. This study aims to explore Maintenance 4.0's impact on sustainable manufacturing performance within a leading Steel Company. Initially, 28 valid indicators were identified through insights from the company's managers. A sequential algorithm combining Fuzzy DEMATEL and Interpretive Structural Modeling (ISM) was then utilized to elucidate the intensity and direction of effects among these indicators. Analysis reveals that the social dimension of sustainable manufacturing has the most significant influence on other sustainability dimensions, while the economic dimension is the most influenced. Real-time communication and collaboration among humans, machines, and sensors emerge as the most potent capability of Maintenance 4.0 for enhancing product sustainability. Operating costs stand out as a key performance indicator. The study underscores the intertwining nature of digitalization and sustainability, highlighting their potential synergy in driving performance indicators within the company. Prior research has predominantly focused on traditional maintenance performance metrics, overlooking the comprehensive effects of Industry 4.0 and its technologies on maintenance and manufacturing performance. This study fills this gap by employing a hybrid Fuzzy DEMATEL-ISM approach.