Investigating the impact of networking capability on firm innovation performance:using the resource-action-performance framework

The author's final peer reviewed version can be found by following the URI link. The Publisher's final version can be found by following the DOI link.Purpose 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. Design/methodology/approach 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. Findings 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. Originality/value 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

Exploring and evaluating success factors of social media marketing strategy: a multi-dimensional-multi-criteria framework

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.Purpose – Today, social media is counted as an integral part of marketing strategies, which has led to a paradigm change in this field. As reported, socialmedia marketing has been growing over the recent five years and is predicted to be exponentially growing in the future. However, despite the huge promise and intention to adopt social media marketing strategies by organisations, there remain challenges regarding the successful implementation of these new marketing programmes. Accordingly, marketing managers’ awareness of the success factors of social media marketing is essential to return investment in this area. Due to the little research been accomplished in this field, this paper aims to identify the success factors of social networks’ marketing and to rank the factors by using of interval best-worstmethod (BWM). Design/methodology/approach – To serve the research aims, an extant literature review is accomplished and a focus group approach is conducted to identify the main success factors and subfactors. To analyse the focus group discussions, a qualitative content analysis approach is applied. Interval BWMis used to calculate the weights of each identified factor. Findings – In the final framework, six main success criteria, including strategy, process, technology, content, performance evaluation and people are identified, for each sub-criteria are developed. The interval BWM results suggest the content criterion as the most important success factor in developing a socialmedia marketing strategy. Research limitations/implications – First, this research provides a comprehensive insight into the success factors and best practices of social media marketing. This is the first to draw on the critical factors affecting the success of social media marketing, considering people in the organisation such as top management, employees and customers, strategy, process and performance evaluation focussing on the change management requirements for applying social media marketing and technology as the technical factor of the adoption process, simultaneously. Identifying critical success factors of social media marketing will help marketing managers to avoid falling into the trap of developing social media strategies based on less important areas and ignoring the critical ones. Besides, owing to the limited resources of organisations in implementing social media marketing strategies, prioritising and weighing the success factors will lead to a focus on more important areas. Originality/value – Whilst the related studies have mostly concentrated on the capabilities and activities required to conduct social media marketing and the few research investigated the critical success factors most concentrated on the customer and the content-related factors, the finding of this research goes beyond that and suggests technical, process and human aspects simultaneously in the implementation process in a holistic view

Robust Multi-Objective Sustainable Reverse Supply Chain Planning: An Application in the Steel Industry

In the design of the supply chain, the use of the returned products and their recycling in the production and consumption network is called reverse logistics. The proposed model aims to optimize the flow of materials in the supply chain network (SCN), and determine the amount and location of facilities and the planning of transportation in conditions of demand uncertainty. Thus, maximizing the total profit of operation, minimizing adverse environmental effects, and maximizing customer and supplier service levels have been considered as the main objectives. Accordingly, finding symmetry (balance) among the profit of operation, the environmental effects and customer and supplier service levels is considered in this research. To deal with the uncertainty of the model, scenario-based robust planning is employed alongside a meta-heuristic algorithm (NSGA-II) to solve the model with actual data from a case study of the steel industry in Iran. The results obtained from the model, solving and validating, compared with actual data indicated that the model could optimize the objectives seamlessly and determine the amount and location of the necessary facilities for the steel industry more appropriately.This article belongs to the Special Issue Uncertain Multi-Criteria Optimization Problem

Strategy Portfolio Optimisation: A COPRAS G-MODM Hybrid Approach

Designing organisational strategies in various businesses is a commonly employed practice; nevertheless, nowadays the strategy portfolio optimisation is one of the major controversial issues. This research proposes an inclusive model to evaluate and select organisational strategies based on the boundaries of its resources. In order to achieve such a model, first of all, a grey COPRAS model is applied to evaluate organisational strategies under uncertain circumstances. Subsequently, on the basis of the aforementioned method, a mixed integer multi-objective linear programming model is depicted to optimise the strategy selection process according to COPRAS-G strategy significance results and with regard to time, cost and other structural constraints as well as organisational policies. Ultimately, a mixed COPRAS G-MODM is transformed to a binary goal programming model and the suggested approach is employed in Iran Mercantile Exchange for strategy portfolio optimisation

Digital transformation and SME internationalisation:unravelling the moderated-mediation role of digital capabilities, digital resilience and digital maturity

PurposeThis study has two main objectives. First, to examine the indirect effects of digital platform capability and digital resilience on digital transformation (DT) outcomes for small- and medium-sized enterprises (SMEs), and second, to investigate how digital business model maturity influences these indirect effects.Design/methodology/approachThe study adopts a quantitative design and collects data through a self-reporting survey from individuals in the technological industries. The Partial Least Squares-Structural Equation Modelling (PLS-SEM) and PLS multi-group analysis examine the measurement and structural models and the significance of differences in indirect paths based on the digital business model maturity level, serving as a moderator.FindingsThe findings of this study provide valuable insights into the internationalisation of digital SMEs. They indicate that digital platform capability and resilience fully mediate, connecting digital resources to SME growth. The study also confirms the digital business model maturity’s positive and significant moderating effect on these indirect relationships.Originality/valueThis research contributes to the existing literature by focusing on the international outcomes of platform ecosystems in developing markets. It explores how digital platform capability and resilience support the digital transformation of SMEs, considering their vulnerability due to their small size. The study also fills a research gap by investigating the relationship between big data, digital leadership and the international growth of digital platforms. Lastly, it explores the role of digital maturity in the relationships between antecedents, determinants and outcomes of digitalisation.<br/

Evaluating strategies for implementing industry 4.0: a hybrid expert oriented approach of B.W.M. and interval valued intuitionistic fuzzy T.O.D.I.M.

open access articleDeveloping and accepting industry 4.0 influences the industry structure and customer willingness. To a successful transition to industry 4.0, implementation strategies should be selected with a systematic and comprehensive view to responding to the changes flexibly. This research aims to identify and prioritise the strategies for implementing industry 4.0. For this purpose, at first, evaluation attributes of strategies and also strategies to put industry 4.0 in practice are recognised. Then, the attributes are weighted to the experts’ opinion by using the Best Worst Method (BWM). Subsequently, the strategies for implementing industry 4.0 in Fara-Sanat Company, as a case study, have been ranked based on the Interval Valued Intuitionistic Fuzzy (IVIF) of the TODIM method. The results indicated that the attributes of ‘Technology’, ‘Quality’, and ‘Operation’ have respectively the highest importance. Furthermore, the strategies for “new business models development’, ‘Improving information systems’ and ‘Human resource management’ received a higher rank. Eventually, some research and executive recommendations are provided. Having strategies for implementing industry 4.0 is a very important solution. Accordingly, multi-criteria decision-making (MCDM) methods are a useful tool for adopting and selecting appropriate strategies. In this research, a novel and hybrid combination of BWM-TODIM is presented under IVIF information

DEA with common set of weights based on a multi objective fractional programming problem

Data envelopment analysis operates as a tool to appraise the relative efficiency of a set of homogenous decision making units. DEA allows each DMU to take its optimal weight in comparison to other DMUs while a similar condition is considered for other units. This feature threats the comparability of different units because different weighting schemes are used for different DMUs. In this paper, a model is presented to determine a common set of weights to calculate DMUs efficiency. This model is developed based on a multi objective fractional linear programming model that considers the original DEA's results as ideal solution and seeks a set of common weights to evaluate DMUs and increases the model's discrimination power. A numerical example is solved and the proposed method's results are compared to some previous methods. This Comparison has shown the proposed method's advantages in ranking DMUs

Game theoretic approach for coordinating unlimited multi echelon supply chains

In order to achieve the overall objectives of the supply chain (SC), there have been seen many contradictions between the components and different levels, and these disorders may result in decreased strength and competitiveness The main contradictions that are considered in this paper comprise inventory, pricing and marketing costs in an unlimited three echelon supply chain. The basics of the game theory make it a suitable and reliable tool for solving contradiction situations by considering all the levels and players’ goals. Initially, an unlimited three echelon supply chain, including S suppliers, M manufacturers, and K retailers, is considered in order to solve the aforementioned problem. Further on, a nonlinear mathematical cooperative model based on specific assumptions, game theory approach, Nash equilibrium definition, Pareto efficiency, and revenue sharing contract is proposed. Subsequently, the proposed model is employed in a numerical example, and the results are illustrated according to the genetic algorithm. Furthermore, the sensitivity of the proposed model is analysed using the design of experiment. Ultimately, the validation of the proposed cooperative model is assessed by the simulatio