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The purpose of this study is to determine whether the fine wine market is efficient between homogeneous lots and heterogeneous lots.

Auction price data for homogeneous (or solid) lots of fine wines was analyzed to create price prediction models. Those models were used to predict the expected auction price for the bottles within heterogeneous lots. Lastly, models were created to explain and predict the differences between expected and realized prices for heterogenous wine lots.

The results show that large inefficiencies exist. The more complex and expensive the heterogeneous lot, the greater the discount relative to what would have been realized if the bottles had been sold individually. This discount can exceed 50% of the expected auction price.

Heterogeneous lots may arise as a practical requirement from the auction house. Restaurant buyers probably have little interest in such lots because of the inclusion of wines the restaurant will be unable to sell. Collectors may be uniquely positioned to benefit from this price discount.

These results are unique in the literature, because the price dynamics of heterogeneous (or mixed) lots of fine wines have not previously been studied.

This study aims to minimize the transportation-related cost in distribution while utilizing a heterogeneous fixed fleet to deliver distinct demand at different geographical locations with a proper workload balancing approach. An increased cost in distribution is a major problem for many companies due to the absence of efficient planning methods to overcome operational challenges in distinct distribution networks. The problem addressed in this study is to minimize the transportation-related cost in distribution while using a heterogeneous fixed fleet to deliver distinct demand at different geographical locations with a proper workload balancing approach which has not gained the adequate attention in the literature.

This study formulated the transportation problem as a vehicle routing problem with a heterogeneous fixed fleet and workload balancing, which is a combinatorial optimization problem of the NP-hard category. The model was solved using both the simulated annealing and a genetic algorithm (GA) adopting distinct local search operators. A greedy approach has been used in generating an initial solution for both algorithms. The paired t-test has been used in selecting the best algorithm. Through a number of scenarios, the baseline conditions of the problem were further tested investigating the alternative fleet compositions of the heterogeneous fleet. Results were analyzed using analysis of variance (ANOVA) and Hsu’s MCB methods to identify the best scenario.

The solutions generated by both algorithms were subjected to the t-test, and the results revealed that the GA outperformed in solution quality in planning a heterogeneous fleet for distribution with load balancing. Through a number of scenarios, the baseline conditions of the problem were further tested investigating the alternative fleet utilization with different compositions of the heterogeneous fleet. Results were analyzed using ANOVA and Hsu’s MCB method and found that removing the lowest capacities trucks enhances the average vehicle utilization with reduced travel distance.

The developed model has considered both planning of heterogeneous fleet and the requirement of work load balancing which are very common industry needs, however, have not been addressed adequately either individually or collectively in the literature. The adopted solution methodologies to solve the NP-hard distribution problem consist of metaheuristics, statistical analysis and scenario analysis are another significant contribution. The planning of distribution operations not only addresses operational-level decision, through a scenario analysis, but also strategic-level decision has also been considered.

The planning of distribution operations not only addresses operational-level decisions, but also strategic-level decisions conducting a scenario analysis.

Online collaboration in today's world is a topic of genuine interest to Internet researchers. The purpose of this paper is to explore the role of group knowledge heterogeneity (GKH) in open collaboration performance using the mediating mechanisms of group cognition (GC) and interaction to understand the determinants of the success of online open collaboration platforms.

Study findings are based on partial least squares structural equation modeling (PLS-SEM), the formal mediation test and moderating effect analysis from Wikipedia's 160 online open collaborative groups.

For online knowledge heterogeneous groups, open collaboration performance is mediated by both GC and collaborative interaction (COL). The mediating role of GC is weak, while the mediating role of COL is strengthened when knowledge complexity (KC) is higher. By dividing group interaction into COL and communicative interaction (COM), the authors also observed that COL is effective for online open collaboration, whereas COM is limited.

These findings suggest that for more heterogeneous large groups, group interaction would explain more variance in performance than GC, offering an in-depth understanding of the relationship between group heterogeneity and open collaboration performance, answering what determines the success of online open collaboration platforms as well as explaining the inconsistency in prior findings. In addition, this study expands the application of Interactive Team Cognition (ITC) theory to the online open collaboration context.

The purpose of this study is to explain the opinions of the Muslim jurists available in the fiqh books so that they may be compared with the approaches adopted by modern scholars for defining the concept of riba. It is argued that the method of jurists was different from the one adopted by the modern Muslim jurists and Islamic economists. The new method dichotomizes riba into those of the Quran and Sunnah. On the contrary, jurists of four Sunni schools considered the Quran and Sunnah in this regard as a single whole, and they saw Sunnah as the elaboration of riba. By explaining the similarities shared by different fiqh schools, it is explained that there is no need for a definition of riba.

The paper uses the method of content analysis. The authors have consulted the authentic fiqh manuals of the four Sunni fiqh schools to substantiate the objectives.

One of the major findings of this paper is that interest charged in loan transactions, including bank loans, is riba according to the four Sunni fiqh schools. Moreover, the paper also shows that the similarities among the four Sunni fiqh schools are far more significant than the often-highlighted disagreements among them regarding the concept of riba. The methodology adopted by modern Muslim scholars seems to add confusions around the concept of riba.

The paper discusses views of only four Sunni fiqh jurists.

The paper explains the common methodology followed by the jurists for understanding riba, the significant similarities resulting from their common method, the link between the concept of riba and different types of financial transactions within the framework of the jurists and that combining several fiqh schools at a time is a contradiction-ridden methodology.

Company goals, behaviors and decision-making processes may differ depending on whether a given company decides to engage in the Industry 4.0 (I4.0) paradigm as a user or as a provider of I4.0-based solutions. This paper will consider this question in-depth by focusing on the extent to which the innovation ecosystem (IES) affects these two main strategies.

The authors' study aims to analyze the impact of a regional information and communication technology (ICT) ecosystem on the implementation of I4.0 at the company level by using an original survey of 123 companies that are already engaged in the implementation of I4.0 in the French region of Hauts-de-France and by employing two sets of logit models.

The authors' empirical study demonstrates the importance of an innovation ecosystem-based strategy for I4.0 technology provision. It reveals that engaging in R&D collaborative projects and developing links and complex relationships with heterogeneous actors within the IES positively affects the likelihood of a given firm deciding to implement I4.0 as a provider of I4.0-based solutions. This does not, however, affect the probability of a firm engaging in the I4.0 paradigm as a user of technologies and solutions.

From a policy standpoint, this study could encourage decision-makers to engage with I4.0 development by developing policies targeting the reinforcement of IES at a regional level. This could also help to accelerate the adoption of I4.0 technologies by manufacturing companies and foster the development of I4.0-based solutions through specific company-targeted policies. The authors' study supports the need for manufacturing company managers to evaluate and identify the best technological strategies related to the I4.0 paradigm that meet their specific needs.

The authors' study shows that the decision to engage in the I4.0 paradigm as providers of I4.0-based solutions is more likely to rely on an innovation ecosystem-based strategy, while the decision to engage in the I4.0 paradigm as users of I4.0-based solutions is more likely to rely on the company’s internal strategies, resources and demand-side benefits.

The purpose of this study is to provide new insights into the relationship between fiscal policy and total factor productivity (TFP) while accounting for several economic and econometric issues of the phenomenon like non-stationarity, fiscal feedback effects, persistence in productivity, country heterogeneity and unobserved global shocks and local spillovers affecting heterogeneously the countries in the sample.

The paper is empirical. It builds an Error Correction Model (ECM) specification within a dynamic heterogeneous framework with common correlated effects and models both reverse causality and feedback effects.

The results of this study highlight some new findings relative to the existing related literature. The outcomes suggest some relevant evidence at both the academic and policy levels: (1) the causal effects going from fiscal deficit/surplus to TFP are heterogeneous across countries; (2) the effects depend on the time horizon considered; (3) the long-run dynamics of TFP are positively impacted by improvements in fiscal budget, but only if the austerity measures do not exert slowdowns in aggregate growth.

The main originality of this study is methodological, with possible extensions to related phenomena. Relative to the existing literature, the gains of this study rely on the way econometric techniques, recently proposed in the literature, are adapted to the economic relationship of interest. The endogeneity due to the existence of reverse causality is modelled without implying relevant performance losses of the models. Moreover, this is the first article that questions whether the effects of fiscal budget on productivity depend on the impact of the former on aggregate output growth, thus emphasising the importance of the quality of fiscal adjustments.

This paper aims to review empirical research on the relationship between institutional ownership (IO) and board governance (85 studies).

Based on agency and upper echelons theory, the heterogeneous monitoring function of specific types and the nature of institutional investors on board composition, compensation and chief executive officer (CEO) characteristics will be focused.

The author found that most studies have referred to archival studies, analyzed the impact of board governance on IO, focused on CEO characteristics, neglected IO heterogeneity and advanced regression models to address endogeneity concerns. In line with the theoretical framework, the relationship between total IO and board governance is heterogeneous. However, specific types such as foreign, dedicated and pressure-resistant institutions represent active monitoring tools and push for increased board governance.

The author provided useful recommendations for future research from a content and methodological perspective, e.g. the need for analyzing the impact of IO on sustainable board governance and other characteristics of top management team members, e.g. the chief financial officer.

As many regulatory bodies implemented regulations to promote shareholder rights and board governance, this literature review highlights the connections of both corporate governance mechanisms. Managers should conduct a careful and timely investor analysis and change the composition and compensation of the board of directors in line with institutional investors’ preferences.

This analysis makes useful contributions to prior research by focusing on IO and board governance, whereas the author structured the heterogeneous variables and results within the structured literature review. The authors guides researchers, regulatory bodies and business practice in this corporate governance topic.

Despite the critical role of the policy environment in facilitating the advancement of building information modeling (BIM) as a systemic innovation to reshape traditional facility design, construction and operation processes, scant scholarly attention has been paid to systematically investigating how and why complex BIM policies are concretely and gradually implemented in different regional contexts from a dynamic policy diffusion perspective. This study aims to empirically investigate how different types of BIM policy instruments are dynamically implemented in heterogeneous regions over time and how the diffusion of BIM policies across different regions is comprehensively impacted by both internal efficiency needs and external legitimacy pressures.

This study employed a positivist research paradigm in which BIM policy data from 182 prefecture-level and above cities in China during 2011–2022 were analyzed with quantitative approaches for theory verification. Based on the content analysis of the evolutionary characteristics of the adopted BIM policy instruments in heterogeneous regions over time, the event history analysis (EHA) method was then used to further examine the mechanisms underlying the diffusion of BIM policies across different regions.

The content analysis results show that while environmental instruments (such as technological integration and goal planning) are the primary policy instruments currently adopted in China, recent years have also witnessed increasing adoptions of supply-side instruments (such as fiscal support and information support) and demand-side instruments (such as demonstration projects and tax incentives). After controlling for the impacts of regional fiscal and technical resources, the EHA results illustrate that BIM policy adoption positively relates to regional construction industry scale but negatively relates to regional industry productivity and that compared with public pressures from industry participants, vertical pressures from the central government and horizontal pressures from neighboring regions are more substantial drivers for policy adoption.

As an exploratory effort of using a dynamic policy diffusion perspective to systematically investigate how BIM policies are adopted in heterogeneous regional contexts to facilitate BIM advancement, this study not only characterizes the complexity and dynamics of BIM policies but also provides deepened understandings of the mechanisms underlying policy adoption in the conservative construction industry. The findings hold implications for how multifarious policy instruments can be more effectively and dynamically adopted to facilitate the advancement of BIM and related technologies as innovative solutions in the construction domain.

This study aims to propose a combined effect framework to explore the relationship between research and development (R&D) team networks, knowledge diversity and breakthrough technological innovation. In contrast to conventional linear net effects, the article explores three possible types of team configuration within enterprises and their breakthrough innovation-driving mechanisms based on machine learning methods.

Based on the patent application data of 2,337 Chinese companies in the biopharmaceutical manufacturing industry to construct the R&D team network, the study uses the K-Means method to explore the configuration types of R&D teams with the principle of greatest intergroup differences. Further, a decision tree model (DT) is utilized to excavate the conditional combined relationships between diverse team network configuration factors, knowledge diversity and breakthrough innovation. The network driving mechanism of corporate breakthrough innovation is analyzed from the perspective of team configurations.

It has been discerned that in the biopharmaceutical manufacturing industry, there exist three main types of enterprise R&D team configurations: tight collaboration, knowledge expansion and scale orientation, which reflect the three resource investment preferences of enterprises in technological innovation, network relationships, knowledge resources and human capital. The results highlight both the crowding-out effects and complementary effects between knowledge diversity and team network characteristics in tight collaborative teams. Low knowledge diversity and high team structure holes (SHs) are found to be the optimal team configuration conditions for breakthrough innovation in knowledge-expanding and scale-oriented teams.

Previous studies have mainly focused on the relationship between the external collaboration network and corporate innovation. Moreover, traditional regression methods mainly describe the linear net effects between variables, neglecting that technological breakthroughs are a comprehensive concept that requires the combined action of multiple factors. To address the gap, this article proposes a combination effect framework between R&D teams and enterprise breakthrough innovation, further improving social network theory and expanding the applicability of data mining methods in the field of innovation management.

The current difficulties of distribution network working robots are mainly in the performance and operation mode. On the one hand, high-altitude power operation tasks require high load-carrying capacity and dexterity of the robot; on the other hand, the fully autonomous mode is uncontrollable and the teleoperation mode has a high failure rate. Therefore, this study aims to design a distribution network operation robot named Sky-Worker to solve the above two problems.

The heterogeneous arms of Sky-Worker are driven by hydraulics and electric motors to solve the contradiction between high load-carrying capacity and high flexibility. A human–robot collaborative shared control architecture is built to realize real-time human intervention during autonomous operation, and control weights are dynamically assigned based on energy optimization.

Simulations and tests show that Sky-Worker has good dexterity while having a high load capacity. Based on Sky-Worker, multiuser tests and practical application experiments show that the designed shared-control mode effectively improves the success rate and efficiency of operations compared with other current operation modes.

The designed heterogeneous dual-arm distribution robot aims to better serve distribution line operation tasks.

For the first time, the integration of hydraulic and motor drives into a distribution network operation robot has achieved better overall performance. A human–robot cooperative shared control framework is proposed for remote live-line working robots, which provides better operation results than other current operation modes.