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The purpose of this paper is to categorize transportation choice research (mode choice and carrier selection) leading to insight on themes in the literature and directions for future research

The proposed transportation choice research categorization framework is based on a comprehensive literature review of the peer‐reviewed journal papers published over the past 20 years, supplemented with a review of practitioner articles to identify current challenges in the logistics field. The academic papers are analyzed in terms of research purpose/question, methodology, findings, and challenges addressed.

The review reveals that several important themes are under‐represented in the transportation choice literature: environmental and energy use concerns; security in the supply chain; supply chain integration; international growth; and the role of the internet and emerging information technologies. This review also found that simulation, case study, and interview methodologies are under‐represented, and that normative modeling research is only lightly represented in this research.

The contributions of this research are three‐fold: the development of a classification scheme for transportation choice research, a structured review that provides a guide to earlier research on the subject of transportation choice, and the identification of research issues for future investigation.

This study aims to elicit the preferences of potential travelers for different property listings' attributes (online review number, positive valence rate of reviews and discount strategy) when selecting hotels and peer-to-peer (P2P) accommodation sharing on online booking platforms.

A discrete choice experiment (DCE) was conducted with 291 respondents with accommodation needs. They were asked to choose between pairs of listings.

The authors found that when booking accommodation online, complex discount strategies were not determinant both in selecting hotels and P2P accommodations. Positive valence rate of reviews has a higher impact on the selection of traditional hotels than P2P accommodations, while the number of online reviews has a higher impact on the selection of P2P accommodations than traditional hotels. The authors further discuss the effect of each attribute on online accommodation selection in terms of price ranges of the property listings.

The findings provide suggestions for platform operators and product/service providers to improve their marketing strategies and optimize their management efforts.

To the best of the authors’ knowledge, this is one of the first studies that investigate the role of property listings' attributes on the selections between hotels and P2P accommodations. The findings from this research study could be generalized to other online platforms and electronic commerce-related transactions.

This paper aims to explore the requirements of organizational knowledge management initiatives using requirements engineering techniques, identifying the optimal techniques configuration and serving as a management tool for knowledge engineers.

The method is selection attributes. Knowledge management enablers are characterized and mapped with the coverage capabilities of requirements engineering techniques, using the attributes of the elicited object and a box-plot analysis. The information is gathered from 280 references, 32 companies and 16 experts in requirements engineering.

Requirements of organizational knowledge management initiatives are got optimally by combining interviews, use cases, scenarios, laddering and focus group techniques. The requirements of structure and processes are more complex to identify, while culture requirements are the best covered.

Knowledge management enablers are analyzed according to the current studies and comprehension of engineering techniques.

Knowledge engineers need to consider the coverage capabilities of engineering techniques to design an optimal requirement identification and meet the objectives of organizational knowledge acquisition initiatives. Requirement engineers can improve the requirements identification by a staged selection process.

The requirements of knowledge management initiatives that impact the community can be identified and traced to ensure the knowledge objectives. Requirements related to culture and people, like shared values, beliefs, and behaviors, are also considered.

To the best of the authors’ knowledge, this is the first study about formal requirement identification of knowledge management initiatives in the organizational context, providing the optimal configuration. A novel staged process is proposed for requirements engineering techniques selection, analyzing the enablers at component level and identifying the attributes associated with the elicited object.

The purpose of this paper is to determine the number of selection criteria of Islamic and commercial banks in Egypt and to identify the relative influence that each attribute may exert on the selection process. Findings indicate differences in the important selection criteria of Islamic and commercial banks in Egypt. Although the number of attributes was similar, differences prevailed in the relative importance of selection criteria. This finding could be linked to the fundamental difference between these two banking systems that are widely spread in the Middle East.

As the popularity of Islamic banking and financial instruments continues to rise globally, a recurring empirical question is what specifically makes consumers choose Islamic banking. This paper aims to investigate the determinants of bank type selection, especially in culturally diverse settings where the Islamic banking sector is well-established. It further examines whether consumers’ gender/religion influences their choices. One intuitive prediction is that Muslim consumers opt for Islamic banking products as “ethical” because of conviction-related reasons. However, the reality is not necessarily straightforward.

This paper uses structural equation modeling to examine data collected from a survey questionnaire of 790 respondents in an emerging market setting. Further analysis is made based on gender and religion to remove related bias.

Results suggest that overall consumer awareness significantly affects the selection of Islamic banking products. The positive effect of awareness is more significant for Muslim consumers relative to non-Muslims. Interestingly, social stimuli and bank attributes have an insignificant effect on the banking choices of both Muslims and non-Muslims.

Results suggest that Islamic banks’ marketing managers should adopt differentiated strategies for men and women, focusing on the core benefits of the service or personal interactions with consumers, respectively, along with a focus on different aspects of personal service for each gender. Awareness should be enhanced by adopting informative and effective marketing strategies to attract and retain consumers in the competitive bank environment. Islamic banks (IB) should pay attention to the religious effect without considering it as the sole variable motivating potential customers. They should design segmented and customized marketing strategies based on gender-religion market segmentation to suit different groups’ needs.

The findings fill a gap in the literature and provide Islamic bankers with insights to help design and articulate their business strategies to appeal to consumers in a multicultural context. Examining an integral part of gender and religion mitigates biased estimates due to the omission of variables. The study contributes to the existing literature on customer preferences for IB with a relatively large, new data set.

The General Society Survey(GSS) is a kind of government-funded survey which aims at examining the Socio-economic status, quality of life, and structure of contemporary society. GSS data set is regarded as one of the authoritative source for the government and organization practitioners to make data-driven policies. The previous analytic approaches for GSS data set are designed by combining expert knowledges and simple statistics. By utilizing the emerging data mining algorithms, we proposed a comprehensive data management and data mining approach for GSS data sets.

The approach are designed to be operated in a two-phase manner: a data management phase which can improve the quality of GSS data by performing attribute pre-processing and filter-based attribute selection; a data mining phase which can extract hidden knowledge from the data set by performing data mining analysis including prediction analysis, classification analysis, association analysis and clustering analysis.

According to experimental evaluation results, the paper have the following findings: Performing attribute selection on GSS data set can increase the performance of both classification analysis and clustering analysis; all the data mining analysis can effectively extract hidden knowledge from the GSS data set; the knowledge generated by different data mining analysis can somehow cross-validate each other.

By leveraging the power of data mining techniques, the proposed approach can explore knowledge in a fine-grained manner with minimum human interference. Experiments on Chinese General Social Survey data set are conducted at the end to evaluate the performance of our approach.

The objective of this paper is to evaluate whether the data from consignors, logistics service providers (LSPs) and consignees contribute to the prediction of air transport shipment delays in a machine learning application.

The research database contained 2,244 air freight intercontinental shipments to 4 automotive production plants in Latin America. Different algorithm classes were tested in the knowledge discovery in databases (KDD) process: support vector machine (SVM), random forest (RF), artificial neural networks (ANN) and k-nearest neighbors (KNN).

Shipper, consignee and LSP data attribute selection achieved 86% accuracy through the RF algorithm in a cross-validation scenario after a combined class balancing procedure.

These findings expand the current literature on machine learning applied to air freight delay management, which has mostly focused on weather, airport structure, flight schedule, ground delay and congestion as explanatory attributes.

This paper aims to address the supplier selection problem based on a developed framework capturing the essence of the supply chain operations reference (SCOR) model, sustainability and providing services to customers. Specifically, the authors consider planning, manufacturing, delivery, sustainability and customer service attributes to evaluate and select suppliers.

Relevant literature is reviewed, a framework capturing the essence of major supply chain functions was developed and suitable measurement attributes were identified. An integrated fuzzy analytic hierarchy process and fuzzy technique for order performance by similarity to ideal solution method are employed to obtain the final ranking of the attributes and suppliers. The proposed methodology is illustrated through a real case of an Indian automobile company.

The authors observed that planning, manufacturing, customer service, sustainability and delivery are preferred in decreasing order to select component suppliers for an automotive company. The impact of suppliers on planning and manufacturing is most important to consider while assessing suppliers. Interestingly, concerns about sustainability and delivery are the least cared factors when selecting suppliers. The top five criteria contain measures of operational efficiency rather than purchasing cost.

This paper proposes and demonstrates a supplier selection framework harmonizing supply chain functions of the SCOR model, sustainability and customers service that adds a valuable wing to literature that expounds on the connection of purchasing strategy to corporate strategy. A case study in an automotive company throws unique and valuable managerial implications for purchasing and supply chain performance.

As the risks associated with sugar-sweetened beverages (SSBs) increase, various policies require sugar to be reduced in beverages. This paper segmented consumers according to food-related lifestyle (FRL), analyzed beverage selection attributes and preference for sugar-reduced beverages (SRBs) for each group and presented basic data for the strategies of SRBs for each consumer group.

In total, 1,000 Korean consumer panels responded to the online survey. The questionnaire consisted of FRL, beverage selection attributes and attitude toward SRBs.

Consumer groups were divided according to FRL: rational, value seeking and careless consumer. Rational consumers tended to be in their 30s or 50s and women, and they focused on product quality/hygiene when choosing beverages. Value seeking consumers were mainly in their 40s and 50s and were characterized by high education and income. They showed high scores in quality/hygiene, economy and sensory traits. Careless consumers were more likely to be in their 20s–30s, unmarried men and considered sensory traits as the most important factor.

The main limitation of this study is the lack of generalization of consumer panels to represent the entire population because they were part of an online research firm.

This study implies that segmenting consumers according to FRL allows detailed analysis of consumer attitudes and behaviors. Using this analysis, the complex consumer pattern can be used as basic data for promoting sugar-reduced beverages.

The purpose of this research is to evaluate the perceptions of local tourists concerning the importance and performance of their dining experience and restaurant selection factors at tourist destinations. Five hundred forty-one questionnaires collected from a series of on-site surveys at popular tourist destinations were analyzed. The results of importance–performance analysis (IPA) illustrate that no attribute fell in the Concentrate Here quadrant; staff service, service speed, food quality, interior design, comfort, cleanliness, restaurant scent, food scent attributes, and the “food service” factor fell under the Keep up the Good Work quadrants; noise, music, new experience, price attributes, and the “servicescape” factor fell in the Low Priority quadrant; servicescape lighting fell in the Possible Overkill quadrant. In conclusion, restaurants at popular tourist destinations have done very well in most service items and seem to have reached the professional standards expected by mass tourists.