Muhammad Hashim

A Fuzzy AHP-TOPSIS Framework for the Risk Assessment of Green Supply Chain Implementation in the Textile Industry

In the emerging supply chain environment, green supply chain risk management plays a significant role more than ever. Risk is an inherent uncertainty and has a tendency to disrupt the typical green supply chain management (GSCM) operations and eventually reduce the success rate of industries. In order to mitigate the consequences, a fuzzy multi-criteria group decision making modeling (FMCGDM) which could evaluate the potential risks in the context of (GSCM) is needed from the industrial point of view. Therefore, this research proposes a combined fuzzy analytical hierarchy process (AHP) to calculate the weight of each risk criterion and sub-criterion and technique for order performance by similarity to ideal solution (TOPSIS) methodology to rank and assess the risks associated with implementation of (GSCM) practices under the fuzzy environment. The proposed fuzzy risk-oriented evaluation model is applied to a practical case of textile manufacturing industry. Finally, the proposed model helps the researchers and practitioners to understand the importance of conducting appropriate risk assessment when implementing green supply chain initiatives.

Impulsive Buying: A Qualitative Investigation of the Phenomenon

The emphasis of this study is to explain the concept of impulsive buying behavior. Numerous definitions and clarifications of the singularities are examined. Impulsive buying had an important factor in the point of view of consumers as well as retailers. Model shown in this study is to classify the conventional IBB and online . Impulse buying behavior. Most of studies have focused only on conventional IBB, thus online IBB remained ignored. Many studies have only focused on impulse buying not retail online impulse buying and its advantages and drawbacks. Present study is important in existing literature as it considers the in depth science behind the impulse buying behavior of customers when they shop traditionally as well as online and also highlights the differentials in both. As online buying behavior is at the verge of becoming a substitute of traditional buying, so it needs to more emphasis of researchers so that fruitful policies can be suggested. Conferring to the results of this study we should know the differences in advantages and disadvantages of conventional impulse purchase and online impulse purchase. This study expands the concepts of IBB in the context of online and its benefits.

Logistics Distribution Centers Location Problem under Fuzzy Environment

Logistics distribution centers location problem is concerned with how to select distribution centers from the potential set for minimizing cost and fulfill the demand. This paper aims at multi-objective optimization for three-echelon supply chain architecture consisting of manufacturer, distribution centers (DCs) and customers. The key design decisions considered are: the number and location of distribution centers, the quantity of products to be shipped from manufacturer to DCs and then from DCs to customers. The present study mainly investigates the proposed problem under fuzzy environment and the uncertain model is converted into a deterministic form by the expected value measure. The approximate best solution of the model is provided using fuzzy simulation. A numerical example is used to illustrate the effectiveness of the proposed model and solution approach.

Risk-Oriented Assessment Model for Project Bidding Selection in Construction Industry of Pakistan Based on Fuzzy AHP and TOPSIS Methods

Risk management for the selection of complex multiple projects during the bidding process is one of the most significant problem in construction industries all over the world. This article develops an evaluation model based on fuzzy set theory, analytical hierarchy process (AHP) and the technique for order performance by similarity to ideal solution (TOPSIS) methods. The criteria weight is achieved by adopting Fuzzy set theory and Analytical Hierarchy Process (AHP). Then, with the minimized risk as the objective, the technique for order performance by similarity to ideal solution (TOPSIS) is applied to determine the final ranking level of the bidding projects according to their closeness coefficient. Finally, a real world application of National Construction Limited (NCL), a largest government oriented company of Pakistan, is conducted to demonstrate the utilization of the proposed model. The results indicate that the proposed model is feasible for risk assessment of project bidding selection in construction industry.

Factors Which Affect the Sustainable Production of Cotton in Pakistan: A Detailed Case Study from Bahawalpur District

Pakistan is one of the most important cotton producing and consuming country in the World. The present study purpose is to explore the important factors affecting cotton production in Pakistan. A sample of cotton growing respondents was randomly selected from different villages of Punjab province. Some production function was employed to assess the effects of education, land fertilization, weather, land preparation, seed, irrigation, etc. On the productivity of cotton. Education, plant protection measures, fertilizer and land preparation were contributing towards higher cotton yield on the sampled respondents farms. So, there is a great need to educate the farmers on priority basis for adopting recommended practices. The extension staff can play a highly positive role in this regard. At the end, a detailed discussion is proposed to show the efficiency of the proposed model.

Production-Distribution Planning in Supply Chain Management Under Fuzzy Environment for Large-Scale Hydropower Construction Projects

In this chapter, production-distribution planning in construction supply chain management is presented under fuzzy environment. This chapter specifically addresses bi-level decision making problem with lower level corresponding to a plant planning problem, while the upper level to a distribution network problem. The main targets of the upper level are to minimize cost and maximize the satisfaction level for concrete mixing plants. The targets of the lower level are to maximize the profit and customer satisfaction level. The model is formulated in terms of fuzzy programming and the best solution is provided by using the fuzzy simulation and sensitive analysis is used to highlight the results. The Neelum Jhelum Hydropower Project is used as a real-world example to illustrate the effectiveness of the proposed approach.

Online Impulse Buying on “Double Eleven” Shopping Festival: An Empirical Investigation of Utilitarian and Hedonic Motivations

“Double Eleven” online shopping festival has become the most celebrated and largest online shopping event in China. This phenomenon originates the need to explore impulse buying behavior in relationship of double eleven festival. This study aims to investigate the structural relationship between hedonic, utilitarian web browsing and online impulse buying behavior on “Double Eleven” shopping festival. Data was collected from 426 online shoppers in six different districts of Beijing. In order to assess the measurement model and to test the hypothesis structural equation modeling was utilized by using AMOS 21. Additionally, Reliability, Discriminant and convergent validity was used for the results of proposed model. The results of this study found that utilitarian and hedonic web browsing positively influence on online impulse shoppers with regard to “Double Eleven” shopping festival in China. To the best of our knowledge, this study is pioneer, aiming at exploring the dynamics of online impulse buying behavior with utilitarian and hedonic predictors with regard to biggest online shopping festival in China. This study provides a deep understanding of e-shoppers toward online impulse behavior in the field of Chinese e-commerce industry that can be generalized to other countries also. Implications for scholars and e-tail managers of our study are discussed.

A Fuzzy Multi-Criteria Group Decision Making Model for Measuring Risks in a Supply Chain Using Extended VIKOR Method

In this paper, we quantify risks in a supply chain process from an aviation’s perspective. Due to globalization, supply chains are getting more and more risky than before. As risk is inherent and uncertain activity, if it occurs then all of the supply chain partners will be impacted with a significant loss. To deal with this problem, a comprehensive risk evaluation index system has been proposed, which captures the level of risk faced by a supply chain in a given situation. For measuring risks in a supply chain we formulated a fuzzy multi-criteria group decision making model based on extended VIKOR method to determine the best feasible solution according to the selected risk parameters. A practical case study is conducted to test the applicability of the proposed methodology. Finally, we discuss the effectiveness of the proposed framework and rank the risk alternatives in descending order.

Multi-objective Optimization Model for Supplier Selection Problem in Fuzzy Environment

Supplier selection decisions are typically multi-objectives in nature and it is an important component of production and logistics management for many firms. The present study mainly investigate a multi-objective supplier selection planing problem in fuzzy environment and the uncertain model is converted into deterministic form by the expected value measure (EVM). This paper aims at multi-objective optimization for minimizing cost and maximizing product quality level. For solving the multi-objective problem a weighted sum base genetic algorithm is applied and the best solution is provided using fuzzy simulation. Finally, a numerical example is used to illustrate the effectiveness of the proposed model and solution approach.

Shopping Online Without Thinking: Myth or Reality

The purposefulness of this study is to assess the relationship between website personality and online impulse buying behavior in Chinese social commerce setting. Further, this paper examines the moderating role of sales promotion between website personality and online impulse buying. Data were collected from three cities of China—Beijing, Shanghai, and Guangzhou. Structure equation modeling was utilized to analyze the measurement model and to test the study hypotheses. Additionally, reliability and validity tests were employed to validate the measurement scale. The findings of this study indicate that website personality is a strong predictor of online impulse buying. Sales promotion and positive affect of emotion, positively and significantly influence on online impulse buying; whereas negative affect of emotion influences negatively. The results suggest that e-tail managers and social application developer of Chinese social commerce should focus on web personality related attributes to induce the consumers to buy impulsively. To the best of authors’ knowledge, this study has not been profoundly conducted in previous literature. This study also strengthens the knowledge of online impulse buying and website features in Chinese social commerce environment. Implications for social commerce marketing and e-tail managers are discussed.