Search results

As ecommerce becomes more prevalent, traditional brick-and-mortar retailers such as warehouse clubs (WCs) face the challenging task of maintaining and growing their customer base. This study aims to unravel the combined impact of retail agglomeration and ecommerce activities on consumer foot traffic (also referred to as “footprint”) at WC stores, placing an emphasis on the locational strategies adopted by WCs in this evolving retail landscape.

Mobile-based customer foot traffic data for Costco, a major U.S. WC chain, is sourced for our analysis. We use Principal Component Analysis (PCA) to identify dimensions of general merchandise (GM) and narrow-range merchandise (NM) retail agglomeration. Two-stage least squares (2SLS) regressions are used to explore how the intensity of ecommerce activities and WC locational choices within retail agglomerations impact WC foot traffic.

Our analysis highlights a notable decline in WC store visits attributable to both GM and NM ecommerce activities, with GM ecommerce presenting a more significant competitive challenge to WCs. Regarding retail agglomerations, proximity to GM clusters that include a diverse range of supercenters, department stores, and club stores, is associated with an increase in WC customer visits within their vicinity. In contrast, the influence of NM agglomerations is mixed; clusters adjacent to grocery stores lead to higher WC customer traffic compared to those focused on other specialized stores. These findings underscore the strategic importance of location in mitigating the adverse effects of ecommerce competition. Additionally, our study uncovers intricate dynamics between GM and NM retail clusters and ecommerce activities, demonstrating varied impacts on WC customer footprint.

Access to customer footprint data illustrates the potential of this data source for retail decision making and researchers. Our analysis is limited to one chain, notably Costco.

Our findings underscore the need for retailers to adeptly navigate the evolving retail landscape, including the confluence between physical and digital retail environments, to secure future success. In particular, our results emphasize the benefits of locating stores within mixed retail agglomerations and underline the need to consider the broader retail landscape in location decisions.

The rise of ecommerce in the U.S. has reshaped consumer behavior and altered local shopping districts’ communal dynamics. This change may spur policy interventions to help physical stores compete with online retailers, emphasizing the importance of retail diversity and community-centric environments to sustain communal retail interactions amidst digital advancements.

The paper makes use of a unique dataset to provide a first assessment of the combined effects of retail agglomeration and ecommerce activities on consumer foot traffic for WC retailers. Thus, this paper provides insights into the impacts on consumer shopping behavior from the dynamic interactions between physical retail clusters and online shopping behaviors.

The small air transport (SAT) domain is gaining increasing interest over the past decade, based on its perspective relevance in enabling efficient travel over a regional range, by exploiting small airports and fixed wing aircraft with up to 19 seats (EASA CS-23 category). To support its wider adoption, it is needed to enable single pilot operations.

An integrated mission management system (IMMS) has been designed and implemented, able to automatically optimize the aircraft path by considering trajectory optimization needs. It takes into account both traffic scenario and weather actual and forecasted condition and is also able to select best destination airport, should pilot incapacitation occur during flight. As part of the IMMS, dedicated evolved tactical separation system (Evo-TSS) has been designed to provide elaboration of both surrounding and far located traffic and subsequent traffic clustering, to support the trajectory planning/re-planning by the IMMS.

The Clean Sky 2-funded project COAST (Cost Optimized Avionics SysTem) successfully designed and validated through flight demonstrations relevant technologies enabling affordable cockpit and avionics and supporting single pilot operations for SAT vehicles. These technologies include the TSS in its baseline and evolved versions, included in the IMMS.

This paper describes the TSS baseline version and the basic aspects of the Evo-TSS design. It is aimed to outline the implementation of the Evo-TSS dedicated software in Matlab/Simulink environment, the planned laboratory validation campaign and the results of the validation exercises in fast-time Matlab/Simulink environment, which were successfully concluded in 2023.

Building information modelling (BIM) implementation in the design, construction and operations (DCO) industry is increasingly becoming essential. While BIM has been adopted on a larger scale in many developed economies, its acceptance is still in the embryonic phases for developing nations in the DCO industry. This study aims to identify the inhibitors to BIM implementation through the social network theoretical lens, intending to understand the associations among the barriers in the Indian context. Subsequently, recommend strategies to mitigate the barriers from the academic practitioner’s perspective.

A mixed methods research was adopted, commencing with comprehensive literature reviews to recognise various inhibitors to BIM implementation. These identified barriers were further examined through the questionnaire survey (n = 71). BIM implementation barrier network (BIBN) was created using University of California at Irvine Network (UCINET) is a powerful social network analysis software that functions on the principle of social network theory. The experts’ opinions were captured through the BIBN network through interviews. Network properties such as eigen vector centrality, betweenness centrality, degree centrality, in-degree and out-degree and clustering coefficient were computed, and the metrics were analysed further.

Twenty-six BIM implementation barriers were initially identified. A questionnaire survey was conducted. The chain reaction can be minimised by prioritising and regulating these barriers. The issues were categorised into fourfold clusters (standardisation, policy and process, cultural and human resources, change management and operational) issues were generated from the exploratory factor analysis (EFA). The obstacles and barriers resulting from the other main barriers associated with it can be minimised by reducing the challenges with high eigenvector centrality but low betweenness importance.

This study proves to accelerate sustainable BIM implementation growth in developing nations; this research study assists BIM stakeholders in developing coping mechanisms to monitor and remove BIM implementation barriers.

Analysing the associativity of the BIM implementation barriers through sociograms for developing nations is a novel concept with this research.

Although research on how the downstream calculations of a patent’s profit potential influence invention renewal decisions is extensive, the impact of the upstream knowledge creation stages is overlooked. The purpose of this study is to address this theoretical vacuum by examining the intra-organizational configuration of knowledge networks and collaboration networks.

The data consist of 491 global pharmaceutical firms that patent in the USA. Drawing on patent records, the authors simultaneously construct intra-organizational knowledge networks and collaboration networks and identify network cohesion features (i.e. local and global). The authors employ panel fixed-effects models to test the hypotheses.

The results show that local knowledge cohesion and local social cohesion decrease invention renewals, while global knowledge cohesion and global social cohesion increase renewals. Moreover, the marginal effects of local and global social cohesion are stronger than those of local and global knowledge cohesion, respectively.

The hypotheses are tested using the pharmaceutical industry as a research setting, which limits the generalizability of our findings. In addition, potential formal and informal contingencies are not considered.

Despite its limitations, this study provides valuable implications. First, managers are cautioned against the adverse effects of local cohesion structures on invention renewal. Second, firms can dynamically adjust their local and global network configuration strategies to harmonize the generation of valuable inventions and the retention of good ideas.

Complementary to previous research that focused on inventions’ performance feedback, this study delves into upstream knowledge creation stages to understand invention renewals.

Previous research has analyzed the consequence of network stability; however, little is known about how partner type diversity influence network stability in R&D network. Based on knowledge-based view and social network theory, the purpose of this paper is to unravel the internal mechanisms between partner type diversity and network stability through the mediating role of knowledge recombination in R&D network.

The authors collected an unbalanced panel patent data set from information communication technology industry for the period 1994–2016. Then, the authors tested the different dimensions of partner type variety and its relevance in the R&D network and the mediating role of knowledge recombination through adopting the multiple linear regression.

Results indicate an inverted U-shaped relationship between partner type diversity (variety and relevance) and network stability, whereas knowledge recombination partially mediate these relationships.

From the perspective of R&D networks, this paper explores that there are the under-researched phenomena the antecedent of network stability through nodal attributes (i.e. partner type variety and partner type relevance). Moreover, this paper empirically examined the mediating role of knowledge recombination in the partner type diversity–network stability relationships. The novel perspective allows focal firm to recognize importance of nodal attributes, which are critical to fully excavate the potential capabilities of cooperating partners in R&D network.

This study aims to use geographical information on social media for public opinion risk identification during a crisis.

This study constructs a double-layer network that associates the online public opinion with geographical information. In the double-layer network, Gaussian process regression is used to train the prediction model for geographical locations. Second, cross-space information flow is described using local government data availability and regional internet development indicators. Finally, the structural characteristics and information flow of the double-layer network are explored to capture public opinion risks in a fine-grained manner. This study used the early stages of the COVID-19 outbreak for validation analyses, and it collected more than 90,000 pieces of public opinion data from microblogs.

In the early stages of the COVID-19 outbreak, the double-layer network exhibited a radiating state, and the information dissemination was more dependent on the nodes with higher in-degree. Moreover, the double-layer network structure showed geographical differences. The risk contagion was more significant in areas where information flow was prominent, but the influence of nodes was reduced.

Public opinion risk identification that incorporates geographical scenarios contributes to enhanced situational awareness. This study not only effectively extends geographical information on social media, but also provides valuable insights for accurately responding to public opinion.

Misinformation can influence decision-making by fueling individual's belief, prejudices, and stereotypes. In the context of international trade, misinformation refers to the spread of false or misleading information and facts mostly with the malicious intent of maligning reputation of products, services, trade policies of a country and thus negatively influencing liberal trade policies toward that country. Stereotypes and prejudices fueled by misinformation coupled with economic nationalism and populism cast a dark shadow over the liberal international order. Exaggerated claims about unfair trade practices laced with stereotypes, prejudices, and misinformation can fuel tensions and may eventually lead to trade dispute and retaliatory action such as the imposition of tariffs or breakdown of trade blocs. Fake News, as a term, came into prominence recently during the 2016 US elections. The spread of fake news during the election generated remarkable interest among researchers. While most research focused on the effect of misinformation, a few studies have shown the influence of misinformation in changing trade preferences. The intricate connection among trading partners can propagate misinformation. Misinformation can lead policymakers to undertake protectionist policies. However, policies driven by misinformation, taken by major economies, can have strong rippling effects on other trading partners because of their strong network connectedness. Therefore, it motivates us to understand and evaluate international trade in terms of network statistics. This chapter provides an in-depth analysis of the network effects of some major and emerging economic powers involved in bilateral or multilateral trade agreements.

Large-scale text-based data increasingly poses methodological challenges due to its size, scope and nature, requiring sophisticated methods for managing, visualizing, analyzing and interpreting such data. This paper aims to propose semantic network analysis (SemNA) as one possible solution to these challenges, showcasing its potential for consumer and marketing researchers through three application areas in phygital contexts.

This paper outlines three general application areas for SemNA in phygital contexts and presents specific use cases, data collection methodologies, analyses, findings and discussions for each application area.

The paper uncovers three application areas and use cases where SemNA holds promise for providing valuable insights and driving further adoption of the method: (1) Investigating phygital experiences and consumption phenomena; (2) Exploring phygital consumer and market discourse, trends and practices; and (3) Capturing phygital social constructs.

The limitations section highlights the specific challenges of the qualitative, interpretivist approach to SemNA, along with general methodological constraints.

Practical implications highlight SemNA as a pragmatic tool for managers to analyze and visualize company-/brand-related data, supporting strategic decision-making in physical, digital and phygital spaces.

This paper contributes to the expanding body of computational, tool-based methods by providing an overview of application areas for the qualitative, interpretivist approach to SemNA in consumer and marketing research. It emphasizes the diversity of research contexts and data, where the boundaries between physical and digital spaces have become increasingly intertwined with physical and digital elements closely integrated – a phenomenon known as phygital.

This study aims to develop an interface management risk interaction modeling and analysis methodology applicable to complex systems in high-speed rail construction projects, reveal the interaction mechanism of interface management risk and provide theoretical support for project managers to develop appropriate interface management risk response strategies.

This paper introduces the association rule mining technique to improve the complex network modeling method. Taking China as an example, based on the stakeholder perspective, the risk factors and significant accident types of interface management of high-speed rail construction projects are systematically identified, and a database is established. Then, the Apriori algorithm is used to mine and analyze the strong association rules among the factors in the database, construct the complex network, and analyze its topological characteristics to reveal the interaction mechanism of the interface management risk of high-speed rail construction projects.

The results show that the network is both scale-free and small-world, implying that construction accidents are not random events but rather the result of strong interactions between numerous interface management risks. Contractors, technical interfaces, mechanical equipment, and environmental factors are the primary direct causal factors of accidents, while owners and designers are essential indirect causal factors. The global importance of stakeholders such as owners, designers, and supervisors rises significantly after considering the indirect correlations between factors. This theoretically explains the need to consider the interactions between interface management risks.

The interaction mechanism between interface management risks is unclear, which is an essential factor influencing the decision of risk response measures. This study proposes a new methodology for analyzing interface management risk response strategies that incorporate quantitative analysis methods and considers the interaction of interface management risks.

The behavior of the entities in a small and medium-sized enterprise (SME) cooperation network is influenced by the core enterprise. Addressing the problem of how the network vulnerability changes when the core enterprise is attacked is a challenging topic. The purpose of this paper is to reveal the failure process of SME cooperation networks caused by the failure of the core SME from the perspective of cascading failure.

According to the Torch High Technology Industry Development Center, Ministry of Science & Technology in China, 296 SMEs in Jiangsu province were used to construct an SME cooperation network of technology-based SMEs and an under-loading cascading failure model. The weight-based attack strategy was selected to mimic a deliberate node attack and was used to analyze the vulnerability of the SME cooperation network.

Some important conclusions are obtained from the simulation analysis: (1) The minimum boundary of node enterprises has a negative relationship with networks' invulnerability, while the breakdown probability has an inverted-U relationship with networks' invulnerability. (2) The combined effect of minimum boundary and breakdown probability indicates that the vulnerability of networks is mainly determined by the breakdown probability; while, minimum boundary helps prevent cascading failure occur. Furthermore, according to the case study, adapting capital needs and resilience in the cooperation network is the core problem in improving the robustness of SME cooperation networks.

This research proposed an under-loading cascading failure model to investigate the under-loading failure process caused by the shortage of resources when the core enterprise fails or withdraws from the SME cooperation network. Two key parameters in the proposed model—minimum capacity and breakdown probability—could serve as a guide for research on the vulnerability of SME cooperation networks. Additionally, practical meanings for each parameter in the proposed model are given, to suggest novel insights regarding network protection to facilitate the robustness and vulnerability in real SME cooperation networks.