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This research has developed a one-stop service supply chain mobile application for the purpose of marketing, product distribution and location-based logistics for elderly farmers and consumers in accordance with the Thailand 4.0 economic model. This is an investigation into the agricultural product distribution supply chain which focuses on marketing, distribution and logistics using the Dijkstra’s and Ant Colony Algorithms to respectively explore the major and minor product transport routes. The accuracy rate was determined to be 97%. The application is congruent with the product distribution, supply chain, in a value-based economy. The effectiveness of the mobile application was indicated to be at the highest level of results of learning outcomes, user comprehension and user experience of users. That is, the developed mobile application could be effectively used as a tool to support elderly farmers to distribute their agricultural products in the one-stop service supply chain which emphasizes marketing, distribution and location-based logistics for elderly farmers and consumers with respect to Thailand 4.0.

As in line with eco benchmarking, the purpose of this paper is to solve a location selection problem in an emerging country by applying sustainability benchmarking principles.

A hybrid multi-criteria decision-making method, fuzzy AHP and Preference Ranking Organization METHod for Enrichment Evaluations (PROMETHEE), is used as methodology to make sustainability benchmarking for logistics center location selection.

It is revealed that according to AHP and PROMETHEE calculations, Kemalpasa is determined as the most appropriate location from the sustainable perspectives. Torbali is specified as the worst location to construct a logistics center in terms of benchmarking criteria based on sustainability concerns. Based on these numerical results, managerial implications are presented with a sustainability benchmarking view.

The main originality of this study is integrating one of the relatively new topics, sustainability benchmarking, with a popular area, logistics center location selection.

The purpose of this paper is to propose a conceptual architecture for the development of an auction business‐to‐consumer marketplace where sellers offer available resources and services aiming to maximize their revenue while on‐the‐move travelers bid for them subject to the geographical area they are located in.

Based on previous findings from the literature and aggregate results from a preliminary field survey, core communication requirements, marketplace architecture, and communication workflows are presented.

Findings from the literature and field study exhibit a great potential for the successful use of location sensitive auction applications in tourism sector. Mobile auctions seem attractive for the efficient allocation and pricing of travel resources by abolishing the internet's barriers related to travelers computing requirements; furthermore, location‐based services (LBS) may reduce significantly the communication costs for sellers. The proposed marketplace is beneficial for a number of stakeholders beyond sellers, like auctioneer, mobile communications providers, and LBS providers.

The proposed architecture is in conceptual form and is currently under development. Infrastructure issues (like communication load, required bandwidth and protocol) are being investigated. Future research will focus on the integration of the architecture in an extended multi‐provider environment forming virtual enterprises. The viability and acceptance of the proposed model should be further investigated through an extended detailed market survey.

To the authors' best knowledge it is the first attempt to propose a location‐sensitive auction marketplace for tourism services.

This paper aims to clarify the spatial connection characteristics and organization mode of logistics economy of 21 cities in Guangdong Province under the background of the integrated development of Guangdong, Hong Kong and Macao Bay area, and explore the spatial development characteristics and influencing factors of logistics economy in Guangdong Province.

This paper constructs the development level model of urban logistics economy in Guangdong Province from three aspects: demand level, supply level and support level, and uses the entropy weight method to measure the development level index of urban logistics economy in Guangdong Province. Then, the traffic accessibility index model is used to measure the traffic accessibility index between cities in Guangdong Province. Finally, using the social network analysis method, combined with the development level index of urban logistics economy in Guangdong Province and the urban traffic access index in Guangdong Province, this paper analyzes the spatial connection characteristics and influencing factors of logistics economy network in Guangdong Province.

There are regional differences in the development level of logistics economy in Guangdong Province; The overall network density of its logistics economic connection is large, but there is an imbalance in the network structure, and the core edge phenomenon is obvious; Logistics economic space presents the characteristics of double core development.

Because the research object is the spatial connection characteristics of logistics economy in Guangdong Province, the research results may lack universality. Therefore, researchers are encouraged to put forward further tests.

By studying the spatial connection mode of logistics economy in 21 cities in Guangdong Province, China, this paper promotes the original methods and empirical contributions, and constructs the research framework of spatial relationship of logistics economy. This research framework is universal to a certain extent.

This paper is conducive to promoting the integrated development of logistics economy in Guangdong Province and improving the balance of regional development of logistics economy.

Firstly, this study provides a new perspective to understand the spatial relationship and spatial spillover of logistics economy from relational data rather than attribute data. Secondly, This study enriched and broadened the research topic of spatial correlation of logistics economy. Thirdly, this research aims to promote the original methods and empirical contributions. Specifically, this study establishes a comprehensive research framework on the spatial network structure of logistics economy.

Logistical facility location decisions can make a crucial difference in the success or failure of a company. Geographical Information Systems (GIS) have recently become a very popular decision support system to help deal with facility location problems. However, until recently, GIS methodologies have not been fully embraced as a way to deal with new facility location problems in business logistics. This research makes a framework for categorizing empirical facility location problems based on the intensity of the involvement of GIS methodologies in decision making. This framework was built by analyzing facility location models and GIS methodologies. The research results revealed the depth of the embracement of GIS methodologies in logistics for determining new facility location decisions. In the new facility location decisions, spatial data inputs are almost always coupled with the visualization of the problems and solutions. However, the usage of GIS capability solely (i.e. suitability analysis) for problem solving has not been embraced at the same level. In most cases, the suitability analysis is used together with special optimization models for choosing among the multiple alternatives.

The purpose of the study is the evaluation of choosing the determined logistics centers’ (LCs’) locations via Multi-Criteria Decision-Making (MCDM) methods.

Since there is more than one criterion in the evaluation of LC location, MCDM methods are used. The Entropy and CRiteria Importance Through Intercriteria Correlation (CRITIC) methods are used to determine the main criteria and sub-criteria weights. The Preference Ranking Organization Method for Enrichment Evaluation (PROMETHEE) method is used for ranking and evaluating 12 alternatives in Turkey and sensitivity analysis according to the threshold values of criteria and preference functions.

Possible LC alternatives in Turkey and 12 locations ranked. Changing the criteria weights at a significant level did not affect the ranking results much. In the sensitivity analysis of the criteria for which market data could not be obtained (scored by the experts) it is found that they either made no difference or made little difference in the ranking of the alternatives.

In terms of sustainability, economic factors along with environmental and social dimensions are important criteria for logistics companies and LC. The use of these variables in the LC location selection makes a difference.

This study focuses on LC location selection, via PROMETHEE with evaluated preference functions for criteria, taking into account nine scenarios that use variable criteria weight calculated via different MCDM methods. The results are evaluated by using sensitivity analysis and taking into account the sustainability aspect for LC. Multiple methods have been used effectively together in a way that support each other.

The balancing of sustainability dimensions is the prime agenda of supply chain organisations. The supply chain sustainability greatly influenced by its freight transport activities. Most of the previous work discussed the economic and environmental sustainability of freight transport industry; although the social sustainability (SS) dimension paid less attention to researchers and practitioners of emerging economies. The purpose of this study is to investigate the importance of SS indicators in the freight transport industry. The SS assessment framework is validated with the Indian freight transport industry.

The proposed framework considers four SS dimension and 25 indicators. The SS indicators’ importance varies with the individual company's prospect. Therefore the proposed framework is used in multi-company perspective as well as in industry perspective to present more realistic results. The importance weight of SS dimension and indicators are computed with a novel multi-criteria decision-making (MCDM) method, i.e. fuzzy best–worst method (FBWM).

The prioritisation of SS indicators in each company perspective is compared with an industry perspective. The contribution to community health and education program is most valuable indicator followed by the prevention of child and forced labour. The model robustness is tested through sensitivity analysis and reported that less variation in indicators’ ranking.

To authors best of knowledge, this is the first study to highlight the importance of SS indicators in the freight transport industry. This study contributes to the sustainability assessment literature by providing a nuanced perception of the SS indicators and put forward managerial implications for improving the SS of the freight transport industry. The proposed framework could be treated as a benchmark for other developing nation's freight transport industry.

This paper aims to examine the relationship between the main decisions for designing distribution centers (DCs) and the contextual characteristics of the distribution networks.

Experts were surveyed and responses analyzed quantitatively through multivariate data techniques. This study considered four contextual characteristics that were deemed as influential for DC design: types of routes in the distribution network, quantity of DCs, distribution network levels and company size.

This paper evidenced which decisions are affected by each contextual characteristic encompassed in this study. This paper identified that the characteristic types of route in the distribution network must be carefully considered, as it had the greatest amount of associations with the decisions for designing a DC.

Despite its importance, most studies on design of DCs disregard the effect of the context in which DCs are inserted. This research provides arguments to support decision-making process of DCs design, increasing assertiveness of their planning. This work fulfills a literature gap by empirically examining the effect of contextual variables on the decisions related to DC design. Regarding practice, this paper addressed a fundamental issue for managers looking to design a DC, as it evidenced how contextual characteristics impact the decision-making.

This study aims to propose an optimal procurement model of the collaborative supply chain in the furniture industry. The final output is the total cost minimisation to produce a furniture product that covers material cost, processing cost, transportation cost and holding cost. Therefore, if companies can give the best value to customers at a low cost, then competitive advantages can be achieved.

A genetic algorithm (GA) as a metaheuristic approach was used to solve problems in this research. The optimisation was initiated by developing a mathematical model to formulate the objective function.

Based on the case study, the proposed GA model was able to reduce the total cost of production. The cost was reduced by 73.09% compared to the existing system. Besides, the production time of the proposed model is within the capacity of both companies; hence, no penalty cost is imposed.

The proposed GA model has been implemented and tested to minimise production costs in the Indonesian furniture industry.

To the best of author knowledge, there is no research has proposed an optimisation model that incorporates production cost, transportation cost and production time capacity together in the collaborative supply chain. This research is the first to collaborate these factors using GA in the furniture industry.

This study’s purpose is to analyze the international mobile marketing (IMK) in order to stage the importance of this tool in the internationalization of companies. Our understanding of mobile marketing is constantly evolving, due to its high business penetration in a world globalized by technologies.

A review of the relevant literature on IMK, companies and customers is undertaken to understand the link between them. The paper begins by explaining the coronavirus disease 2019 is accelerating the change of the rules of the game in traditional and online commerce around the world. Furthermore, this study uses secondary data from organisation for economic co-operation and development (OECD), Sensor Tower, mobile marketing association (MMA), App Annie, among others, to support research results.

The results have shown that IMK has opened a melting pot of opportunities for companies and consumers in this period of pandemic; the potential of this tool is being redefined, in order to identify, anticipate and satisfy customers requirement profitably and efficiently. This study aims to provide an assessment of new concept of IMK and how this tool has to be integrated into the firm’s digital marketing strategies.

The study contributes to make better future decisions in the international digital expansion of companies by company executives and marketing experts. This paper provides a comprehensive framework intended to guide research efforts focusing on digital marketing as well as to aid practitioners in their quest to achieve IMK success.