High-tech companies are rapidly growing in the world. Research and development (hereafter R&D) department strength is the main asset that allows a firm to achieve a competitive advantage in high-tech businesses. The allocated budget to this sector is finite; thus, integration, human resource, risk and budget limitations should be considered to choose the most valuable project in the best portion of time. This paper investigates a case study from a high-tech company in Iran to prioritize the most attractive technologies for the R&D department. The case consists of twenty three technology options and the goal is to find the most attractive projects to sort them out for implementation in the R&D department. In this research, scholars proposed the best-worst method (henceforth BWM) to find the weight of the criteria of the attractive technologies in first step and utilize the newly developed method total area based on orthogonal vectors (henceforward TAOV) to sort the selected technologies based upon the identified criteria. Project integration is one of the least-noticed subjects in scientific papers; therefore, the researchers presented a zero or one linear programming (ZOLP) model to optimize and schedule the implementation procedure on the project risk, budget and time limitation simultaneously. The results indicate that starting few but attractive projects in the first years and postponing the rest to the future, helps a firm to manage funds and gain profit with the least amount of risk.

Purpose Knowledge management seeks collaborative practices among organisations to generate technical, adapt and share knowledge to obtain a sustainable competitive advantage in cross-border business activities. This paper aims to disentangle the crucial determinants of knowledge management in inter-organisational arrangements settings. Design/methodology/approach In the first stage, after an in-depth literature review, the main knowledge management drivers are identified. In the second stage, based on the identified drivers, the importance and relationship between the drivers are evaluated by expert opinions from academic and executive activists. Eventually, in the last stage, a multi-layer decision-making approach has been proposed and used to determine the relationship and the importance of the drivers. Findings The findings of this paper assess the ranking of the different elements from experts’ opinions and discuss important theoretical and managerial implications. The influential factors were identified through an extensive literature review, which combined with the views of experts from academia and industry (international firms). Furthermore, the ranking of factors based on the experts’ overall opinion was used to discuss theoretical and managerial contributions. Originality/value This research provides a better understanding of the interrelationships between the key drivers of knowledge management, which helps management draw more effective strategies to address the cultural differences between firms. Moreover, understanding of the importance of the systems and structures that define the nature of the collaboration in inter-organisational settings, as well as the risks related to those are presented in this research.

Prominent influence of transportation costs on supply chain overall profit indicates the importance and emergence of transportation optimization models. Regarding this issue and in view of realistic situation consisting of non-deterministic information, in this research optimizing inbound and outbound transportation costs of a multi echelon supply chain has been considered. To deal with uncertain time deliveries and pricing strategies adopted by different members of supply chain, in conjunction with unpredictable demand rate, fuzzy logic and specifically Trapezoidal Fuzzy Numbers (TrFNs) are included. After designing a fuzzy binary multi objective model based upon structural assumptions, the solving approach is proposed and the model is employed on Iranian steel supply network to illustrate the potential and advantages of our scheduled model. The bi-objective mixed integer fuzzy programming model presents and encompasses many realistic circumstances making the model applicable in network transportation cases.

We propose a game‐theoretic approach to examine several possible coalition strategies in a four‐echelon supply chain consisting of a supplier, manufacturer, wholesaler, and retailer. A solitude model is used to probe the role of learning in quality improvements, and experimental design is conducted to evaluate all possible supply chain coalition strategies between echelons. The novelty of this study is the comprehensive evaluation of knowledge‐sharing strategies in collaborative supply chains. The results confirm that the Delta model with a coalition among a supplier, manufacturer, and retailer is the best strategy.

PurposeDue to the political, economic and infrastructure barriers and risks that international entrepreneurs (IEs) face when researching an emerging economy's agrifood sector, this research aims to identify the major barriers, analyse their relationships, quantify their importance, classify and rank them. Thus, the IEs will gain a better understanding and vision of their decision-making processes in this era.Design/methodology/approachTo do this, the authors first created a list of barriers to entry for IEs into Iran's rising economy's agrifood industry. Following that, a multi-layer decision-making approach was developed and implemented to accomplish the research objectives. The first stage utilized a hybrid of interpretive structural modelling (ISM) and cross-impact matrix multiplication applied to classification (MICMAC) to depict the level-based conceptual model and classification of the IEs’ obstacles to entry into the agrifood sector. Following that, a hybrid decision-making trial and evaluation laboratory (DEMATEL), and analytic network process (ANP) called DANP was utilized to present a causal relationship between the barriers, identify their causes and effects, and also quantify the relevance of each barrier.FindingsAfter employing the multi-layer decision-making approach, the results demonstrated that fundamental limitations, including infrastructure and technology limitations, are the most critical barriers alongside policy factors encompassing governmental support and access to global or regional economy/market. According to the results, innovation and economic sustainability of the agrifood supply chain also matter. All of these critical barriers are intertwined and should be planned and solved simultaneously. Furthermore, based on DANP results, the sustainability pillars (economy, environment, society), besides the low efficiency of the agrifood sector in Iran, should be investigated further for future policy makings.Originality/valueA hybrid multi-layer decision-making approach has been used for analysing the barriers of investment in the agrifood sector of the emerging economy of Iran for the international entrepreneurs. Moreover, the authors provide implications and insights for IEs and officials for decision-making in the future.

The critical impact of electricity on the quality of human life and the use of all electrical appliances and equipment is in principle self-evident. Nevertheless, governments cannot afford even productivity to consumption. The countries developed many structures to operate and improve the city and industrial electricity consumption and to manage power generation efficiency. Increase in population and the culture of consumption force the governments to raise the price. However, it is difficult to find ways and means to effectively manage trends in public behaviour and to control the harmful action of the population. This process requires knowing the need and consumption of electricity. The article discusses the primary criterion that influences electricity consumption and uses the singular spectrum analysis based on these factors to predict use. Besides, a fuzzy regression model is represented to optimise function. Results of optimisation show a considerable reduction in comparison with SSA forecasting method, indicating the efficiency of the offered method. Eventually results considerably assume that attention to a way of construction and improvements of the culture of use is a priority of the persons making decisions to reduce radical electric consumption in Iran and to become more optimistic concerning management of an electrical network.

This review aims to assess the most prevalent disruptive technologies of the past decade and evaluate them from a dual perspective. This study utilises the technology life cycle framework to classify disruptive technologies into three phases, (i) emerging, (ii) industry, and (iii) customer‐focused research outcomes. Subsequently, entities using six thematic categories via topic modelling are assessed to determine the research trajectory about customers, industries, and theory. The present study utilises the Latent Dirichlet Allocation framework for topic modelling, a quantitative tool that employs advanced statistical methodology to extract semantic knowledge from large text corpora. This approach offers a more comprehensive and insightful categorisation of information compared to traditional research review models such as archive review, meta‐review analysis, and systematic literature review. After the review, over 750 articles were analysed and classified according to their unique themes and technological emphasis. The study suggests practical applications that could enhance industrial progress through disruptive technology. Furthermore, by identifying gaps, the authors suggest multiple research prospects for forthcoming investigations on disruptive technologies and their impact on consumer behaviour. This research is novel in various aspects. This research is by far the only research record in the last decade that provides a systematic literature review of disruptive technologies with an extensive focus on customers. Considering the methodological perspective, this research uses topic modelling as a new literature review model, enabling analysing more research outputs and yielding more valuable findings than traditional methodologies.

Following the outbreak of the Covid-19 pandemic, there was a serious need for the pharmaceutical industry to combat the disease more quickly and effectively. In this regard, numerous companies set out to repurpose current drugs. The noticed decision has major challenges in various dimensions, including the creation and management of an efficient supply chain. The present study attempts to examine the significance and relationships of the repurposing challenges and analyze the effectiveness of supply chain coordination contracts confronting them. In this regard, a combination of Decision-Making Trial and Evaluation Laboratory (DEMATEL) and Analytic Network Process (ANP) named DANP method is applied to investigate the relationships and extracting the weights of the mentioned challenges and the multi-criteria optimization and compromise solution technique called VIKOR is employed to prioritize the supply chain coordination contracts found on their impact facing with repurposing challenges. The mentioned techniques have been conducted under the condition of linguistic Z-numbers. The results demonstrated that financial support and digitalization are the most influential challenges. Moreover, collaboration and data availability have the most weight. In addition, four contracts including effort sharing, cost-sharing, credit option and buyback are the best contracts that companies in the merging economy of Iran should concentrate on them. This research proposes a novel framework of decision-making by integrating DANP and VIKOR with linguistic Z-numbers. Additionally, this study takes a new look at the use of coordination contracts from the viewpoint of repurposing challenges which is highlighted particularly during the Covid-19 pandemic.