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The role of inter-organizational knowledge mechanisms (IOKMs) in learning networks is increasing so that the competition of business networks in providing innovations is highly dependent on the effective selection and application of these mechanisms. This study aims to argue that recognizing the classification of IOKMs and understanding their impact on networking capability (NC) makes the selection of mechanisms more effective.

With a systematic review of literature, a comprehensive list of IOKMs, their main characteristics and NCs have been extracted. The authors have used a focus group for data gathering and a hybrid multi-layer decision-making approach for data analysis. Finally, the impact of IOKMs on NC was determined.

By implementing a multi-layer decision-making approach, four categories of IOKMs including person-to-person, co-creation, team-oriented and informational are illustrated and their effects of NC are determined. Therefore, the findings of this research provide latecomer firms (LCFs) managers with a clear framework for selecting IOKMs.

The literature review shows that the number of knowledge mechanisms, especially their inter-organizational types, is increasing. It has made it difficult for LCFs managers to select effective and efficient mechanisms. Most of these mechanisms are listed, and few studies have classified them. Besides, research shows that fewer studies have investigated how IOKMs relate to NC. Furthermore, most studies on IOKMs have been conducted in the context of leading firms and LCFs have been neglected.

The experience of successful firms has proven that one of the most important ways to promote co-learning and create successful networked innovations is the proper application of inter-organizational knowledge mechanisms. This study aims to use a resource-action-performance framework to open the black box on the relationship between networking capability and innovation performance. The research population embraces companies in the Iranian automotive industry.

Due to the latent nature of the variables studied, the required data are collected through a web-based cross-sectional survey. First, the content validity of the measurement tool is evaluated by experts. Then, a pre-test is conducted to assess the reliability of the measurement tool. All data are gathered by the Iranian Vehicle Manufacturers Association (IVMA) and Iranian Auto Parts Manufacturers Association (IAPMA) samples. The power analysis method and G*Power software are used to determine the sample size. Moreover, SmartPLS 3 and IBM SPSS 25 software are used for data analysis of the conceptual model and relating hypotheses.

The results of this study indicated that the relationships between networking capability, inter-organizational knowledge mechanisms and inter-organizational learning result in a self-reinforcing loop, with a marked impact on firm innovation performance.

Since there is little understanding of the interdependencies of networking capability, inter-organizational knowledge mechanisms, co-learning and their effect on firm innovation performance, most previous research studies have focused on only one or two of the above-mentioned variables. Thus, their cumulative effect has not examined yet. Looking at inter-organizational relationships from a network perspective and knowledge-based view (KBV), and to consider the simultaneous effect of knowledge mechanisms and learning as intermediary actions alongside, to consider the performance effect of the capability-building process, are the main advantages of this research.

To design a novel hybrid approach to illustrate a reciprocal alignment to integrate future products and technologies. This mixed qualitative-quantitative method aims to optimize the final product portfolio and production technologies alignment in the food industry.

A list of products and technologies is extracted and evaluated by experts employing Market Attractiveness and Ease of Implementations Matrix (MA-EI) for products and attractiveness and technological Capability Matrix (A-C) for technologies. Weights of high-scored alternatives are attained applying the Z-number extension of Best Worst Method (ZBWM). After the product-technology matrix is formed and the alignment scores of each pair are determined by experts. Subsequently, final scores are computed, and a framework is proposed by electing high-ranked products and technology of each cluster to form the aligned product and technology portfolios of a food and hygiene industry company.

By employing an uncertain multicriteria decision-making approach besides product and technology matrices in a food industry corporation, among 40 technology and product, 13 products by 6 technologies are proposed. Thus, only six technology are necessary to manufacture the highly important and effective products.

The combination of product and technology analysis matrixes with an uncertain decision-making approach is considered as a novel approach in this research. Moreover, the distinctness between the present study and other researches is the concurrent unified aspect of product portfolio and technology optimization and its implementation in the planning discussion, especially in the food industry.

Nowadays, quality is one of the most important key success factors in the automobile industry. Improving the quality is based on optimizing the most important quality characteristics and usually launched by highly applied techniques such as failure mode and effect analysis (FMEA). According to the literature, however, traditional FMEA suffers from some limitations. Reviewing the literature, on one hand, shows that the fuzzy rule-base system, under the artificial intelligence category, is the most frequently applied method for solving the FMEA problems. On the other hand, the automobile industry, which highly takes advantages of traditional FMEA, has been deprived of benefits of fuzzy rule-based FMEA (fuzzy FMEA). Thus, the purpose of this paper is to apply fuzzy FMEA for quality improvement in the automobile industry.

Firstly, traditional FMEA has been implemented. Then by consulting with a six-member quality assurance team, fuzzy membership functions have been obtained for risk factors, i.e., occurrence (O), severity (S), and detection (D). The experts have also been consulted about constructing the fuzzy rule base. These evaluations have been performed to prioritize the most critical failure modes occurring during production of doors of a compact car, manufactured by a part-producing company in Iran.

Findings indicate that fuzzy FMEA not only solves problems of traditional FMEA, but also is highly in accordance with it, in terms of some priorities. According to results of fuzzy FMEA, failure modes E, pertaining to the sash of the rear right door, and H, related to the sash of the front the left door, have been ranked as the most and the least critical situations, respectively. The prioritized failures could be considered to facilitate future quality optimization.

This research provides quality engineers of the studied company with the chance of ranking their failure modes based on a fuzzy expert system.

This study utilizes the fuzzy logic approach to solve some major limitations of FMEA, an extensively applied method in the automobile industry.

Literature survey shows that it is not clear how knowledge management capability (KMC) and ambidexterity capability affect entrepreneurial creativity (EC) and entrepreneurial intensity (EI) promotion. While empirical studies have emphasized the importance of these factors in improving business performance, the cumulative effect and self-reinforcing loops of these factors in improving firm performance have not been identified. In this regard, the study seeks to investigate how to increase the entrepreneurial capabilities of KMC, EI, EC and ambidexterity of food firms to improve their performance.

The method of the present study is applied in terms of purpose and is quantitative in terms of data collection. In order to collect the data, a questionnaire was designed that contained the variables of the conceptual model of the research. This questionnaire was distributed among industrial and academic experts in the Iranian food industry. The method of data collection is an online cross-sectional survey, and the method of data analysis is structural equation modeling using Smart PLS software to analyze the conceptual model.

The present study is cross-sectional survey research that examines the impact of KMC, EC and EI on firm performance by considering the mediating role of organizational ambidexterity. The research study shows a positive impact of entrepreneurial capabilities as KMC, EI, EC and ambidexterity on performance. Accordingly, if a firm builds KMC and fosters EC, it can achieve ambidextrous innovation and thus enhance its EI and performance in the food industry.

This study highlights the knowledge-based view (KBV) in explaining the role of KMC on innovative capabilities and its influence on performance. Research findings shed light on the importance of KMC as a prerequisite for innovation strategy. The study has also established the mediating role of ambidexterity in entrepreneurial value creation. According to the results, small and medium-sized enterprises (SMEs)' performance is positively influenced by entrepreneurial capabilities as KMC, EI, EC and ambidexterity.

This paper gives insights into how SMEs can improve their performance to gain a competitive advantage by developing knowledge and creative ideas in line with entrepreneurial goals. In this regard, the food industry can adopt new strategies to reduce the impact of these challenges to achieve superior performance and competitive advantage.

The purpose of this paper is to scrutinize the existing literature and provide a comprehensive overview by compiling and synthesizing the dispersed body of knowledge in the networking capability (NC) literature stream. Therefore, this review study contributes to the research by presenting a summary of the NC complex construct.

The authors have tried to cover the literature gap in the NC area through a systematic review.

The theoretical contributions of this study to the NC literature stream are fourfold. First, while critically reviewing existing definitions, the authors present an integrated definition of NC. Second, the authors delineate the conceptual boundary between NC and other similar capabilities. Third, the authors found that the focal firms’ NC consists of two key dimensions: network development capability (NDC) and network management capability (NMC). Fourth, they contribute to the literature by providing a set of suggestions for further research in the NC literature stream.

This study has some limitations, like other review studies. First, although the authors have tried their best to conduct a comprehensive literature search, they may have missed a study. Second, it should be noted that this study has confined itself to a particular stream of literature. Undoubtedly, in other streams, there will be issues similar to the concepts discussed in this study. The main purpose of this study is to integrate a series of studies that have a common theoretical foundation and fall within a particular literature stream. Although the focus of this study may be positive, it can be said that the deprivation of achievements from other similar streams is one of the limitations of this study. Third, another limitation of this study is the lack of verification of the conceptual framework derived from the literature that needs to be addressed in future research.

This study suggests a set of practical implications for industrial managers. First, the authors summarize the firms’ capabilities needed to develop and manage networks in one single source. Based on the conceptual framework of this study, firms can develop managerial tools, technological options, checklists and questionnaires and monitor the status of NC in their surrounding network on an ongoing basis. Second, the present research shows that some NCs are more repetitive than others, and therefore, it can be said that managers should pay more attention to them. The critical NCs, such as determining network position, determining network size, partner selection and attraction, coordination, inter-firm knowledge sharing and conflict resolution, are included in this study. Third, the argument of this study that both NDC and NMC should be considered simultaneously can be thought of as an important practical implication. Although in terms of the network life cycle, NDC is required earlier than NMC, these two capabilities should be used in parallel. Managers should not expect network development to be perfect and then network management to begin; therefore, NMCs should be used during network development.

Research shows that most network studies focus more on network antecedents and outputs and less on processes and related capabilities. Some researchers have made few efforts to identify and scrutinize capabilities related to business relationships. In this context, IMP scholars have introduced NC to emphasize the network perspective. Despite the considerable conceptual and empirical richness, the existence of different nomenclatures and theoretical diversity in NC literature has led to conceptual ambiguity and a lack of consensus on this crucial complex construct.