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The purpose of this paper is to understand how reverse resource exchanges and resource dependencies are managed in the service supply chain (SSC) of returnable transport packaging (RTP).

A single case study was conducted in the context of automotive logistics focusing on the RTP SSC. Data were collected through 16 interviews, primarily with managers of a logistics service provider (LSP) and document analysis of contractual agreements with key customers of the packaging service.

Resource dependencies among actors in the SSC result from the importance of the RTP for the customer’s production processes, the competition among users for RTP and the negative implications of the temporary unavailability of RTP for customers and the LSP (in terms of service performance). Amongst other things, the LSP is dependent on its customers and third-party users (e.g. the customer’s suppliers) for the timely return of package resources. The role of inter-firm integration and collaboration, formal contracts as well as customers’ power and influence over third-party RTP users are stressed as key mechanisms for managing LSP’s resource dependencies.

A resource dependence theory (RDT) lens is used to analyse how reverse resource exchanges and associated resource dependencies in SSCs are managed, thus complementing the existing SSC literature emphasising the bi-directionality of resource flows. The study also extends the recent SSC literature stressing the role of contracting by empirically demonstrating how formal contracts can be mobilised to explicate resource dependencies and to specify, and regulate, reverse exchanges in the SSC.

The research suggests that logistics providers can effectively manage their resource dependencies and regulate reverse exchanges in the SSC by deploying contractual governance mechanisms and leveraging their customers’ influence over third-party RTP users.

The study is novel in its application of RDT, which enhances our understanding of the management of reverse exchanges and resource dependencies in SSCs.

Returnable transport packaging (RTP) solutions have found increasing attention in the recent past. It is not clear, however, under what conditions an RTP system improves a company's financial performance. This paper investigates the operational factors that influence the financial attractiveness of an RTP solution in a manufacturing environment and discusses how these factors are related to each other.

The paper presents the results of five empirical RTP use cases and compares the case study findings with the results found in literature in order to develop a taxonomy of RTP cost effects. Drawing on the concept of value-based management (VBM), the operational drivers of these RTP cost effects are systematized and categorized in a value driver model that relates RTP cost effects to overall economic value added (EVA).

Based on the use case findings, additional cost factors are identified that have not been previously discussed in literature. The amended taxonomy of influence factors is further operationalized in a value driver model.

The present paper is the first one providing a taxonomy of RTP cost effects and putting these effects in a conceptual framework that can be used for decision-making and performance benchmarking.

The purpose of this paper is to seek an efficient method to tackle the energy provision problem for smart grid with sparse constraints and distributed energy and storage devices.

A complex smart grid is first studied, in which sparse constraints and the complex make-up of different energy consumption due to the integration of distributed energy and storage devices and the emergence of multisellers are discussed. Then, a real-time pricing scheme is formulated to tackle the demand response based on sparse bilevel programming. And then, a bilevel genetic algorithm (BGA) is further designed. Finally, simulations are conducted to evaluate the performance of the proposed approach.

The considered situation is widespread in practice, and meanwhile, the other cases including traditional model without the sparse constraints can be seen as its extensions. The BGA based on sparse bilevel programming has advantages of “no need of convexity of the model.” Moreover, it is feasible without the need to disclose the private information to others; therefore, privacies are protected and system scalability is kept. Simulation results validate the proposed approach has good performance in maximizing social welfare and balancing system energy distribution.

In this paper, the authors consider the sparse constraints due to the fact that each user can only choose limited utility companies per time slot. In reality, there exist some other sparse cases, which deserve further study in the future.

To the best of the authors’ knowledge, this is one of the very first studies to address pricing problems for the smart grid with consideration of sparse constraints and integration of distributed energy and storage devices.

This paper presents a non‐intrusive method of determining network performance parameters for voice packet flows within a Voice over IP, or Internet Telephony call. An advantage of the method is that it allows not only end‐to‐end performance monitoring of flows, but also makes it possible to inspect the transport parameters of a specific network or link when delay sensitive traffic transits through it. The results of a preliminary test, to check the validity of the method, are also included.

Sales and market share of store brands have been growing significantly at the expense of national brands. The decision to purchase a store brand or a national brand has been modeled in this paper. The proposed model provides an explanation for the existence of asymmetric price competition between store brands and national brands. The article proposes and empirically demonstrates the existence of a reference threshold as the key criterion underlying this choice. It also shows that the decision to buy the store/national brand is not influenced by the store brand’s price or price promotions, or the magnitude of the difference between the threshold and the national brand’s price.

The study aims to investigate the effect of entrepreneurial leadership (EL), competencies (ECs) and intentions (EIs) on enterprise performance (EP) via entrepreneurial resilience (ER) and risk-taking propensity (RTP).

Data were collected from 403 early-stage small and medium enterprise (SME) owners in Pakistan at two-time intervals and were analyzed using AMOS 22.

All predictors (i.e. EIs, EL and ECs) positively affected EP and ER, except for EL and ER. Furthermore, RTP and ER were serially mediated in linking EIs and ECs with EP but could not establish a link between EL and EP.

The findings reveal that the Pakistani government and business owners must focus on SMEs’ sustained development and prioritize ECs.

This paper is unique in nature, as understanding EIs, EL and ECs in a holistic framework has never been tested before in relation to EP.

Examines consumer preferences for forthcoming technological innovations. Studies consumer response to different levels of technology over time. Looks at preferences for existing and intermediate technologies when future ones are expected. Focuses on technological consumer durables that are expected to evolve over time. The primary contributions of this research are: an understanding of how consumer preferences for a technology are affected by the time of adoption; an understanding of the value to consumers of obtaining different levels of a technology, at different points in time; and the utilization of parsimonious indices to assess consumer response to different levels of technology over time. An empirical examination is conducted for high definition television (HDTV). Using survey data, the study explores consumer preferences for HDTV, and for interim television technologies. Managerial implications to aid product design, and the timing of introduction of evolving technological innovations, are also discussed.

This paper examines the impact of a blockchain platform on the role and importance of trust in established buyer-supplier relationships.

A literature review provides insight into trust development in supply chains. Research uses a case study of two wine supply chains: the producers, importers, logistics companies and UK Government agencies. Semi-structured interviews determine how trust and trustworthiness develop in buyer-supplier relationships and the impact of a blockchain-based technology proof of concept on supply chain trust.

A blockchain-based platform introduces common trusted data, reducing data duplication and improving supply chain visibility. The platform supports trust building between parties but does not replace the requirements for organisations to establish a position of trust. Contrary to literature claims for blockchain trustless disintermediation, new intermediaries are introduced who need to be trusted.

The case study presents challenges specific to UK customs borders, and research needs to be repeated in different contexts to establish if findings are generalisable.

A blockchain-based platform can improve supply chain efficiency and trust development but does not remove the need for trust and trust-building processes. Blockchain platform providers need to build a position of trust with all participants.

Case study research shows how blockchain facilitates but does not remove trust, trustworthiness and trust relationships in established supply chains. The reduction in information asymmetry and improved supply chain visibility provided by blockchain does not change the importance of trust in established buyer-supplier relationships or the trust-based policy of the UK Government at the customs border.

Considering the varied and dynamic workload of vessel traffic service (VTS) operators, design an adaptive rotating shift solution to prevent them from getting tired while ensuring continuous high-quality services and finally guarantee a benign maritime traffic environment.

The problem of rotating shift in VTS and its influencing factors are analyzed first, then the framework of automatic identification system (AIS) data analytics is proposed, as well as the data model to extract spatial–temporal information. Besides, K-means-based anomaly detection method is adjusted to generate anomaly-free data, with which the traffic trend analysis and prediction are made. Based on this knowledge, strategies and methods for adaptive rotating shift design are worked out.

In VTS, vessel number and speed are identified as two most crucial factors influencing operators' workload. Based on the two factors, the proposed data model is verified to be effective on reducing data size and improving data processing efficiency. Besides, the K-means-based anomaly detection method could provide stable results, and the work shift pattern planning algorithm could efficiently generate acceptable solutions based on maritime traffic information.

This is a pioneer work on utilizing maritime traffic data to facilitate the operation management in VTS, which provides a new direction to improve their daily management. Besides, a systematic data-driven solution for adaptive rotating shift is proposed, including knowledge discovery method and decision-making algorithm for adaptive rotating shift design. The technical framework is flexible and can be extended for managing other activities in VTS or adapted in diverse fields.

The purpose of this paper is to extend the existing literature on entrepreneurial intentions (EIs) by employing the integrated model of personality traits and the theory of planned behavior (TPB). It further examines the mediating role of TPB’s dimensions between personality traits and EIs of final-year university students in two diverse economies: China and Pakistan.

The paper uses a survey method for data collection, administered both in electronic and paper form. The authors use structural equation modeling and the partial least square (PLS) method on a sample of 1,016 students and present PLS path modeling, mediation analysis and multigroup analysis.

Results reveal several differences regarding personality traits and TPB on EIs across the two countries. The impact of TPB was positive and significant in both countries; however, TPB demonstrated more explaining power in China’s student sample. Using three personality traits (risk-taking propensity, proactive personality and internal locus of control) as antecedents to TPB, the results reveal a stronger influence of personality traits among Chinese students. The mediation of three dimensions of TPB also revealed differences between country samples.

This is the first study of its kind to compare and contrast the differences between EIs in terms of personality and the determinants of planned behavior among university students in two diverse economies. The integrated model is original, supports both TPB and personality factors and provides a valuable perspective through its findings on two culturally diverse Asian countries. By applying the model in two different cultures, this study distinguishes the results for the two economies from those conducted in other economies.