The impact of learning orientation on innovation performance: mediating role of operations strategy and moderating role of environmental uncertainty

Performing well in developing production industry is an important factor for companies to survive and sustain a competitive edge in the current turbulent business environment. The purpose of this study is to explore the effect of learning orientation on innovation performance with the mediating role of operations strategy (cost, quality, flexibility, and delivery). Environmental uncertainty plays a moderator role in this model. Using a questionnaire to measure variables, data were collected from 243 UK production companies. Structural Equations Modelling used for data analysis and hypothesis testing. The results support 9 out of thirteen research hypotheses. Learning orientation influences innovation performance and two dimensions of operations strategy (delivery and quality) mediates this relationship. Also, environmental uncertainty positively moderates the relationship between quality and flexibility strategies with innovation performance.N/

An interpretive structural modeling—analytic network process approach for analysing green entrepreneurship barriers

Entrepreneurship is one of the issues that plays a key role in the economic growth and development of countries. This economic development and technological advancement have caused environmental damage, which has led entrepreneurs to move towards sustainable production and green entrepreneurship. There are, however, challenges and barriers in front of green entrepreneurs. Hence, this article aims to identify the barriers and challenges of green entrepreneurship in Iran and explore their Interactions and prioritization. To achieve this goal, two quantitative and qualitative approaches were used. In the qualitative approach, using the Fuzzy Delphi method and using expert opinions in this field, 16 factors were identified. In the quantitative phase, the ISM-ANP combination approach was used. First, Interpretive Structural Modeling (ISM) was used to analyze the Interactions between these factors. Finally, using the ISM output, the analytic network process (ANP) method was used to prioritize these barriers. The results showed that the factor of reducing budget allocations and investing in green entrepreneurship in the first priority and the factor of high investment costs in the last priority. Given that so far few studies have been conducted in Iran on the barriers to green entrepreneurship, this paper provides a basis for understanding the various factors that prevent the implementation of green entrepreneurship. Also the analysis of these barriers by using the ISM-ANP approach is a new attempt and important in the field green entrepreneurship

An analytic network process model to prioritize supply chain risks in green residential megaprojects

Megaprojects and specifically ‘green’ construction of residential megaprojects can contain significant risks of failure. To design proper risk mitigation strategies, after identifying key risk factors, the next step is to conduct assessments that would facilitate the process of risk element prioritization. Risk assessment comprises the establishment of factor interrelation and discerning the indicators of importance. This research proposes a novel version of an integrated prioritization method and analyzes twelve all-inclusive key supply chain oriented risk factors identified in a previous study. Through a comprehensive literature review three criteria, impact, probability, and manageability are selected. Also, a fourth criterion namely influence rate is included in the model, based on the driving powers that can also be derived from the Interpretive Structural Modeling’s (ISM) assessment. Fundamentally, the calculations hinge on the Analytic Network Process (ANP) method which provides an assessment of the alternatives’ weights based on pairwise comparisons concerning the criteria specified. To enhance the accuracy of the perceptive judgments of the expert panelists, a bell-shaped fuzzy function is used to convert the verbal statements to crisp values. In addition, Row Sensitivity Analysis is administered to check the stability of the results and provide predictive scenarios. To validate the model, a case study, located in Iran, was conducted, where an expert panel consisting of four individuals made the pair-wise comparisons through an ANP questionnaire. Results indicate priority and sensitivity of the alternatives concerning criteria, for the case under study

Effect of Absorptive Capacity on Strategic Flexibility and Supply Chain Agility: Implications for Performance in Fast-Moving Consumer Goods

This paper develops a model to examine the relationships between absorptive capacity (ACAP), strategic flexibility (SF), supply chain agility (SCA), and firm performance (FP) based on the resource-based view (RBV) and the dynamic capabilities view (DCV). Using structured questionnaire, a sample of 186 randomly selected firms in fast-moving consumer goods (FMCG) industry from both Turkey and Iran as two developing countries is used to test the hypotheses. Variance-based structural equation modeling (SEM) was the primary data analysis method. The results show that absorptive capacity has direct and indirect effects on performance with the mediator variables of supply chain agility and strategic flexibility. Moreover, increased absorptive capacity leads to increased supply chain agility that in turn improves performance. The effect of absorptive capacity on strategic flexibility, and also, the overall proposed conceptual model, especially in the FMCG industry are the original features of the current study which was conducted in two developing countries. Efforts to promote absorptive capacity can improve both strategic flexibility and supply chain agility which are effective factors for enhancing performance in the fast-changing environment of FMCG industry

A triple bottom line approach for designing a sustainable closed-loop supply chain network in fruit industry: A metaheuristic solution approach

In this study, the design of a sustainable closed-loop supply chain network for agricultural products with the goals of minimizing the cost and emission of greenhouse gases and maximizing the response to customer demand, and creating justice-based job opportunities, simultaneously, are aimed. The intended chain is based on the fruit supply chain study, which includes fresh fruits, concentrate, and vermicompost fertilizer. A mixed-integer linear programming (MILP) model has been developed to achieve the triple bottom line. Due to the nature of the NP-hard problem, the proposed model is solved using metaheuristic approaches consisting of two renowned algorithms, NSGA-II and NRGA, and a relatively new algorithm called NSGA-III. It is worth noting that the parameters of the algorithms are adjusted to achieve the best performance in small, medium, and large-size problems exerting the Taguchi method. After comparing the results of the three algorithms based on the well-known criteria, NRGA is introduced as the superior algorithm. Ultimately, the results of sensitivity analysis indicate that appending the possibility of using vermicompost in gardens and considering several vehicles in the proposed sustainable supply chain boosts the values of economic and environmental objective functions to about 6.4 and 8.2%, respectively