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This paper aims to deepen the understanding of robust food supply chains (FSC) in SMEs by exploring and analyzing the literature through the lenses of digital technologies.

The study collected data from Scopus spanning from 2010 to 2024, employing selected keywords, and processed it using VOS-viewer and Biblioshiny to derive valid inferences and theoretical arguments.

The review paper identified several key themes shaping the future of supply chain management – Sustainability in SCM, Industry 4.0, Digitalization with FSCM, Circular Economy, Food Waste with Supply Chain, Food Security and Climate Change. These themes collectively bring transformative opportunities for both the adoption of digital technologies and sustainable practices in food supply chains.

The review found limitations are rooted in financial constraints, institutional barriers and expertise-related challenges encountered within the realm of Digitalization and FSC. Government and corporate houses should focus on these limitations as well as convert them to strengthen the SMEs of FSC.

The study stands out as a pioneering review that not only explores Digitalization in FSC but also explores the link and evidence of SMEs in the unorganized sector, providing unique insights into a previously underexplored area.

The objective of the study is to develop a methodology to strategically rank store locations using criteria such as population, store site characteristics, economic considerations, competition and so on to select the most optimal retail convenience store location.

A case of National Capital Region, India, for a 24-h convenience store was considered for the study and the major criteria that affect the performance of a convenience store are identified, such as population characteristics, economic criteria, competition, consumer accessibility, store size, total cost, site attractiveness and security. Fuzzy AHP is utilized to find the weightage for each criteria and a combination of fuzzy TOPSIS and grey relational analysis (GRA) is applied to rank the alternative using these criteria weight. Further, results obtained are compared with results from fuzzy TOPSIS and fuzzy VIKOR methods. Sensitivity analysis is also performed for ensuring the robustness of the framework.

It is observed that outcomes do not change under various settling coefficient values, demonstrating that the methodology is very robust. The developed framework will be quite useful to diverse retailers looking to expand and generate substantial profits.

A large sample size of number of locations encourages generalization of results. Strategic ranking of the selected locations is carried out on a few selected criteria. The study was limited by the designated geographical area.

The study contributes to the few available articles on convenience store selection using combination of fuzzy AHP, fuzzy TOPSIS and GRA for a developing country.

The purpose of this paper is to reveal the paradox between diversification and specialization from a dynamic perspective. More precisely, this paper will analyze the impact of diversification and specialization as well as their interaction on regional innovation in different development stages.

Based on the principles of new economic geography and innovation geography, data from 30 provinces from 2001 to 2017 was used to explore the relationship. Least squares regressions with fix effect were used to examine the hypotheses.

The results show that both diversification and specialization have a significant and positive impact on regional innovation. The interaction of diversification and specialization also significantly and positively impacts regional innovation. The effect of industrial agglomeration is heterogeneity under different development stages.

This paper verifies the positive role of diversification and specialization and their interaction in promoting regional innovation. The impact of industrial agglomeration on innovation is dynamic and changes with the regional development process. Emerging economies should make appropriate industrial agglomeration strategies according to their development stages.

This paper introduces diversification, specialization and their interaction into the research framework at the same time to analyze their impact on innovation performance which deepened the research of industrial agglomeration. Taking China as an example, this paper also examines the impact of industrial agglomeration on regional innovation in different development stages that expands the dynamic perspective of industrial agglomeration.

This work aims to explore why people review their experienced online shopping in such a manner (promptness), and what is the potential relationship between the users’ review promptness and review motivation as well as reviewed contents.

To evaluate the customers’ responses regarding their shopping experiences, in this paper, the “purchase-review” promptness is studied to explore the temporal characteristics of users’ reviewing behavior online. Then, an aspect mining method was introduced for assessment of review text. Finally, a theoretical model is proposed to analyze how the customers’ reviews were formed.

First, the length of time elapsed between purchase and review was found to follow a power-law distribution, which characterizes an important number of human behaviors. Within online review behaviors, this meant that a high frequency population of reviewers tended to publish relatively quick reviews online. This showed that the customers’ reviewing behaviors on e-commerce websites may have been affected by extrinsic motivations, intrinsic motivations or both. Second, the proposed review-to-feature mapping technique is a feasible method for exploring reviewers’ opinions in both massive and sparse reviews. Finally, the customers’ reviewing behaviors were found to be mostly consistent with reviewers’ motivations.

First, the authors propose that the “promptness” of users in posting online reviews is an important external manifestation of their motivation, product experience and service experience. Second, a semi-supervised method of review-to-aspect mapping is used to solve the data quality problem in mining information from massive text data, which vary in length, detail and quality. Finally, a huge amount of e-commerce customers’ purchase-review promptness are studied and the results indicate that not all product features are responsible for the “prompt” posting of users’ reviews, and that the platform’s strategy to encourage users to post reviews will not work in the long term.

This study aims to examine the impact of the decision makers’ risk preference on logistics routing problem, contributing to logistics behavior analysis and route integration optimization under uncertain environment. Due to the unexpected events and complex environment in modern logistics operations, the logistics process is full of uncertainty. Based on the chance function of satisfying the transportation time and cost requirements, this paper focuses on the fourth party logistics routing integrated optimization problem considering the chance preference of decision makers from the perspective of satisfaction.

This study used the quantitative method to investigate the relationship between route decision making and human behavior. The cumulative prospect theory is used to describe the loss, gain and utility function based on confidence levels. A mathematical model and an improved ant colony algorithm are employed to solve the problems. Numerical examples show the effectiveness of the proposed model and algorithm.

The study’s findings reveal that the dual-population improvement strategy enhances the algorithm’s global search capability and the improved algorithm can solve the risk model quickly, verifying the effectiveness of the improvement method. Moreover, the decision-maker is more sensitive to losses, and the utility obtained when considering decision-makers' risk attitudes is greater than that obtained when the decision-maker exhibits risk neutrality.

In an uncertain environment, the logistics decision maker’s risk preference directly affects decision making. Different parameter combinations in the proposed model could be set for decision-makers with different risk attitudes to fit their needs more accurately. This could help managers design effective transportation plans and improve service levels. In addition, the improved algorithm can solve the proposed problem quickly, stably and effectively, so as to help the decision maker to make the logistics path decision quickly according to the required confidence level.

Considering the uncertainty in logistics and the risk behavior of decision makers, this paper studies integrated routing problem from the perspective of opportunity preference. Based on the chance function of satisfying the transportation time and cost requirements, a fourth party logistics routing integrated optimization problem model considering the chance preference of decision makers is established. According to the characteristics of the problem, an improved dual-population ant colony algorithm is designed to solve the proposed model. Numerical examples show the effectiveness the proposed methods.