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Using real-time support systems may help operators in road construction to improve paving and compaction operations. Nowadays, these systems transform from descriptive to prescriptive systems. Prescriptive or operator guidance systems propose operators actionable compaction strategies and guidance, based on the data collected. It is investigated how these systems mediate the perceptions and actions of operators in road pavement practice.

A case study is conducted on the specific application of an operator guidance system in a road pavement project. In this case study, comprehensive information is presented regarding the process of converting input in the form of data from cameras and sensors into useful output. The ways in which the operator guidance systems translate data into actionable guidance for operators are analyzed from the technological mediation perspective.

Operator guidance systems mediate actions of operators physically, cognitively and contextually. These different types of action mediation are related to preconditions for successful implementation and use of these systems. Coercive interventions only succeed if there is widespread agreement among the operators. Persuasive interventions are most effective when collective and individual interests align. Contextual influence relates to designs of the operator guidance systems that determine human-technology interactions when using them.

This is the first study that analyzes the functioning of an operator guidance system using the technological mediation approach. It adds a new perspective on the interaction between this system and its users in road pavement practice.

We consider a joint optimization problem of product platform design and scheduling on unrelated additive/subtractive hybrid machines, and seek to find efficient solution approaches to solve such problem.

We propose a mathematical formulation for the problem of simultaneous product platform design and scheduling on unrelated additive/subtractive hybrid machines, and develop a simulated annealing-based hyper-heuristic algorithm with adjustable operator sequence length to solve the problem.

The simulated annealing-based hyper-heuristic algorithm with adjustable operator sequence length (SAHH-osla) that we proposed can be quite efficient in solving the problem of simultaneous product platform design and scheduling on unrelated additive/subtractive hybrid machines.

To the best of our knowledge, we are one of the first to consider both cost-related and time-related criteria for the problem of simultaneous product platform design and scheduling on unrelated additive/subtractive hybrid machines.

Reducing the number of generated mutants by clustering redundant mutants, reducing the execution time by decreasing the number of generated mutants and reducing the cost of mutation testing are the main goals of this study.

In this study, a method is suggested to identify and prone the redundant mutants. In the method, first, the program source code is analyzed by the developed parser to filter out the effectless instructions; then the remaining instructions are mutated by the standard mutation operators. The single-line mutants are partially executed by the developed instruction evaluator. Next, a clustering method is used to group the single-line mutants with the same results. There is only one complete run per cluster.

The results of experiments on the Java benchmarks indicate that the proposed method causes a 53.51 per cent reduction in the number of mutants and a 57.64 per cent time reduction compared to similar experiments in the MuJava and MuClipse tools.

Developing a classifier that takes the source code of the program and classifies the programs' instructions into effective and effectless classes using a dependency graph; filtering out the effectless instructions reduces the total number of mutants generated; Developing and implementing an instruction parser and instruction-level mutant generator for Java programs; the mutant generator takes instruction in the original program as a string and generates its single-line mutants based on the standard mutation operators in MuJava; Developing a stack-based evaluator that takes an instruction (original or mutant) and the test data and evaluates its result without executing the whole program.

The logistics industry has undergone a tremendous transformation. This transformation is necessary to cope with the fundamental changes in customer expectations and the need for digitalization imposed by the pandemic, changes in the socioeconomic world, and innovative technology solutions. This paper aims to present digital transformation as an integrated framework for transforming the operating model and applying advanced solutions to the ecosystem of a quintile logistics (5PL) company. 5PL operators are typically an ecosystem. Loosely coupled or self-organized entities that collaborate in a symbiotic relationship represent this ecosystem. They aim to jointly develop capabilities, create innovative services or solutions, share knowledge, facilitate transactions, and leverage network synergies in a logistics environment to provide optimized or novel customer- or partner-centric solutions (Lamberjohann and Otto, 2020).

Currently, there is no single definition of an integrated logistics operations model in 5PL practice, so the qualitative method used in this paper allows for investigation from an exploratory perspective. The paper follows a qualitative research methodology, collecting and analyzing data/facts through interviews and visits to subject matter experts, industry practitioners, and academic researchers, combined with an extensive review of academic publications, industry reports, and written and media content from established organizations in the marketplace. This paper follows a qualitative research methodology, as it is an inquiry rather than a statistical study. The qualitative method allows the study of the concepts of phenomena and definitions, their characteristics, and the defining features that serve as the basis (Berg, 2007). It emphasizes generalized interpretation and deeper understanding of concepts, which would be more difficult in quantitative, statistically based research. Fact-finding was conducted in two ways: in-depth interviews with experts from academia, information and communication technology organizations, and key players in the logistics industry; and academic publications, industry reports, and written and media content from established national and international organizations in the market.

The operations model introduced considers six aspects: persons, processes, platforms, partners, protection and preservation. A virtual team approach can support the personal side of the 5PL ecosystem’s digital transformation. Managing a 5PL ecosystem should be based on collaborative planning, forecasting, and replenishment methods (Parsa et al., 2020). A digital platform can support trust among the stakeholders in the ecosystem. A blockchain solution can powerfully support the 5PL ecosystem from partner relationships’ points of view. The implementation of a cybersecurity reference model is important for protection (Bandari, 2023). Reverse logistics and an integrated approach support the preservation of the ecosystem.

While the author has experience applying the different components of the operations model presented, it would be interesting to find a 5PL that would use all the components presented in an integrated way. The operations model presented applies to any similar ecosystem with minor adaptations.

This paper addresses operations models and digital transformation challenges for optimizing 5PL operators. It provides several opportunities and considerations for 5PL operators interested in improving their management and operations to cope with the growing challenges of today’s world.

The competitiveness and long-term performance of 5PL operators depend on selecting and carefully implementing their operations models. This paper emphasizes the importance of using advanced operations models.

The operations model derives from the author’s personal experiences in research and the innovative application of these models to logistics operators (DHL, UPS, Poste Italiane and others). This paper brings together academic and industry perspectives and operations models in an integrated business digital transformation. This paper defines an original optimal operations model for a 5PL operator and can add sustainable value to organizations and society. In doing so, it outlines different solution requirements, the critical success factors and the challenges for solutions and brings logistical performance objectives when implementing a digital business transformation.

Accurate prediction of seasonal power consumption trends with impact disturbances provides a scientific basis for the flexible balance of the long timescale power system. Consequently, it fosters reasonable scheduling plans, ensuring the safety of the system and improving the economic dispatching efficiency of the power system.

First, a new seasonal grey buffer operator in the longitudinal and transverse dimensional perspectives is designed. Then, a new seasonal grey modeling approach that integrates the new operator, full real domain fractional order accumulation generation technique, grey prediction modeling tool and fruit fly optimization algorithm is proposed. Moreover, the rationality, scientificity and superiority of the new approach are verified by designing 24 seasonal electricity consumption forecasting approaches, incorporating case study and amalgamating qualitative and quantitative research.

Compared with other comparative models, the new approach has superior mean absolute percentage error and mean absolute error. Furthermore, the research results show that the new method provides a scientific and effective mathematical method for solving the seasonal trend power consumption forecasting modeling with impact disturbance.

Considering the development trend of longitudinal and transverse dimensions of seasonal data with impact disturbance and the differences in each stage, a new grey buffer operator is constructed, and a new seasonal grey modeling approach with multi-method fusion is proposed to solve the seasonal power consumption forecasting problem.

The highlights of the paper are as follows:

1. A new seasonal grey buffer operator is constructed.

2. The impact of shock perturbations on seasonal data trends is effectively mitigated.

3. A novel seasonal grey forecasting approach with multi-method fusion is proposed.

4. Seasonal electricity consumption is successfully predicted by the novel approach.

5. The way to adjust China's power system flexibility in the future is analyzed.

A new seasonal grey buffer operator is constructed.

The impact of shock perturbations on seasonal data trends is effectively mitigated.

A novel seasonal grey forecasting approach with multi-method fusion is proposed.

Seasonal electricity consumption is successfully predicted by the novel approach.

The way to adjust China's power system flexibility in the future is analyzed.

The phenomenal proliferation of crowdfunding platforms raises concerns on the heightened occurrence of financial crimes since billions of funds are exchanged through these online systems frequently. Accordingly, some countries have implemented legislative responses to address these risks, although each countries’ laws have varying degrees of severity. Hence, the purpose of this study is to assess the efficiency and robustness of Mauritian laws to combat financial crimes that may arise from a crowdfunding transaction with a particular emphasis on money laundering and tax evasion.

To achieve this research objective, the black letter approach was used to analyse Mauritian rules and regulations on the researched topic and a comparative analysis was carried out against the corresponding laws on crowdfunding in some other jurisdictions, notably the UK and the USA with the view of suggesting the policy recommendations to Mauritian authorities.

It was found that there is still scope for improving the existing legal and regulatory framework on crowdfunding in Mauritius to prevent instances of money laundering and tax evasion. The paper suggests that a crowdfunding operator must be categorised as a reporting person and must carry out regular due diligence checks. There must also be more collaboration in terms of information exchanges and training sessions among the tax authority of Mauritius, crowdfunding operators, fund seekers and investors to shed light on the tax treatment of income and deductions to avoid issues of tax evasion.

At present, to the best of the authors’ knowledge, this study is amongst the first academic writings on the efficiency of Mauritian laws in dealing with the risk of financial crimes through crowdfunding, and also, because existing literature is quite scarce on assessing the adequacy of crowdfunding rules in developing countries, this research aims at filling in the gap in literature. The study is carried out with the aim of combining a large amount of empirical, theoretical and factual information that can be of use to various stakeholders and not only to academics.

With increasing wine consumption in Armenia, both residents and inbound tourists have become attractive target groups for wine sales, which are stimulated by wine tourism activities. The objective of this explorative study is to shed light on the potential of wine tourism for rural development in Armenia.

The paper starts with a structured and interdisciplinary literature review. Based on qualitative surveys among local tour operators and wine producers, and complemented by three expert interviews, the offer of wine tourism activities in Armenia will then be analyzed.

Each of the surveyed wine producers offers wine tourism activities. Foreign tourists know little about the Armenian wine industry, however, and are interested in cultural experiences and Armenia’s breathtaking nature. Armenian wine producers need to understand the expectations of their target groups to develop or adapt their offers successfully.

Due to the explorative nature of this study, the sample size of the surveyed wineries and tour operators is small and hence not representative. In addition, only local tour operators were surveyed. The sample should be extended to include foreign tour operators and more wineries in future research projects.

Whereas first studies on the structure and competitiveness of the Armenian wine sector exist, there is no survey on the general wine tourism in Armenia and its potential to foster rural development.

The rapidly growing e-commerce industry with its special characteristics brings new challenges to the optimization of the supply chain and inventory management. This study aims to investigate the inventory-related optimization of an e-marketplace official store that works on a business-to-customer system when cashback promotion is used to attract more customers. Also, it proposes a new inventory model to maximize the e-commerce profit by optimizing the cashback amount and delivery period.

The proposed model assumes that customer demand is a function of price and delivery time and that price is affected by the cashback amount. The e-commerce operator has a profit-sharing contract with an e-payment company that facilitates the payment. E-commerce also builds collaboration under a cost-sharing contract with a supplier to ensure product delivery. A mathematical model is developed and the related theories are investigated. A numerical example illustrates the validity of the model and a sensitivity analysis is carried out to give useful insights.

A new inventory model for an e-market system has been introduced which shows the impact of a cashback promotion on the e-commerce business. This study shows that managers can optimize the cashback amount and its delivery time to get the maximum profit. In certain cases, the manager may set a high cashback amount (e.g. 100%) to attract customers to place more orders.

This study presents a new inventory model for today’s fast-growing e-commerce business; therefore, the results contribute to the understanding of promotion program practices and inventory management and provide insights to develop efficient e-commerce managerial decisions.

This study aims to investigate the consequences of middle managers’ sensegiving for organisational change in neglected workplaces, where middle managers are given insufficient resources because of receiving low attention from top management.

The authors conducted a case study of three call centres in the Japanese non-life insurance industry. To collect data, the authors conducted interviews with ten stakeholders and made multiple field observations.

The authors identified the following mechanism: in neglected workplaces, middle managers initially focus on sensegiving to employees because they recognise the difficulty of eliciting support from top management. However, as a result, they see sensegiving to employees as top priority and do not try to elicit the support of top management, which is necessary for further organisational change. As a result, organisational change stops at a certain level.

The authors identified the following mechanism: in neglected workplaces, middle managers initially focus on sensegiving to employees because they recognise the difficulty of eliciting support from top management. However, as a result, they see sensegiving to employees as their top priority and do not try to elicit the support of top management, which is necessary for further organisational change. As a result, organisational change stops at a certain level.

First, this study contributes to the body of research on the effects of sensegiving on organisational change. It shows the new problems hidden behind organisational change, which existing research merely regards as independent successes. Second, this study identifies middle managers’ behaviour during organisational change in neglected workplaces. Instead of focusing on the factors necessary for successful organisational change, as in existing studies, this study extends the knowledge of the role of middle managers in organisational change by focusing on their behaviours when success factors are not aligned.

To extend research into sport consumer behaviors related to online sports betting, this study is designed to identify and examine the relationship between online sports betting motivations and online sports betting intentions. By applying a push-pull framework from online sport consumption and gambling studies, nine motivations to engage in online sports betting were identified. These motivations were hypothesized to motivate online sports betting intentions.

A quota sampling technique based on the sports bettor demographics available in the American Gaming Association (AGA, 2019) and the Pew Research Center (2022) obtained a total of 550 completed surveys that met the inclusion and exclusion criteria. For data analyses, confirmatory factor analysis (CFA) and structural equation modeling (SEM) were used to examine the measurement model and the hypothesized model, respectively.

The results revealed that four motivations (i.e. monetary gain, excitement, convenience and negative technology-readiness) were related to online sports betting intention, while five motivations (i.e. sport fandom, positive technology-readiness, impulsivity, socialization and promotion) were not.

The results provide foundational theoretical knowledge of what motivates sports fans to participate in online sports betting. Furthermore, the findings assist practitioners in their allocation of resources by enhancing their understanding of online sports betting motivations.