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1 – 10 of 15Marco Picone, Michele Amoretti and Francesco Zanichelli
A large set of valuable applications, ranging from social networking to ambient intelligence, may see their effectiveness and appeal improved when supported by the large‐scale…
Abstract
Purpose
A large set of valuable applications, ranging from social networking to ambient intelligence, may see their effectiveness and appeal improved when supported by the large‐scale, real‐time tracking of mobile devices, either carried by humans or embedded into vehicles. A centralized approach, where few servers would collect position data and provide them to interested consumers, would hardly cope with the resource demand of the foreseen huge increase of users interested in location‐based services and with the flexibility needs of emerging user‐generated services. The purpose of this paper is to propose a decentralized peer‐to‐peer approach to cope with these requirements, for which positioning information flows directly among mobile devices incurring in limited data exchange.
Design/methodology/approach
The authors propose a decentralized peer‐to‐peer approach for which positioning information flows directly among mobile devices incurring limited data exchange. A peer‐to‐peer overlay scheme is introduced called distributed geographic table (DGT), where each participant can effectively retrieve node or resource information (data or service) located near any chosen geographic position. Next, the authors describe a DGT‐based localization protocol that allows each peer to proactively discover and track all peers that are geographically near to itself.
Findings
The authors provide a performance analysis of the protocol by simulating several 1,000 users that move across an urban area according to realistic mobility models. The results show that the solution is effective, robust, scalable and highly adaptable to different application scenarios.
Originality/value
The new contributions of this paper are a general framework called DGT, which defines a peer‐to‐peer strategy for mobile node localization, and a particular instance of the DGT that supports applications in which every node requires to be constantly updated about the location of its neighbors.
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Pasquale Massimo Picone, Marco Galvagno and Vincenzo Pisano
There is growing interest in how hubris bias shapes managerial and entrepreneurial judgments and decisions and, in turn, firm strategy and performance. Based on a 44-years dataset…
Abstract
Purpose
There is growing interest in how hubris bias shapes managerial and entrepreneurial judgments and decisions and, in turn, firm strategy and performance. Based on a 44-years dataset of articles reaching the beginning of 2023, the authors offer a synthesis of hubris research published within business journals.
Design/methodology/approach
The authors implement a mixed-method approach offering a content representation of 600 peer-reviewed articles extracted from Scopus. The authors conduct a bibliometric investigation – employing Excel, VOSViewer and Biblioshiny software – and perform a qualitative review.
Findings
The analysis unveils four thematic clusters: hubris bias in financial policies (Cluster 1), hubris bias in restructuring deals (Cluster 2), hubris bias in entrepreneurial contexts (Cluster 3) and hubris bias in strategic decision-making (Cluster 4). Moreover, the authors infer that hubris research in business predominantly developed from three disciplinary perspectives – finance, entrepreneurship and strategic management – and progressed with limited interdisciplinary dialogue.
Practical implications
The authors call practitioners' attention to the impact of the hubris bias in forming financial, entrepreneurial and strategic choices. Managers get conscious of the risks of hubristic choices; hence, they implement organizational practices that move forward with unbiased (or less biased) judgments and decisions.
Originality/value
The authors offer an up-to-date and comprehensive view of hubris research in business. Furthermore, the authors provide an integrative framework and a research agenda.
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Looks at the first 100 years of Italian cinema examining its role in Italy’s recent history. Provides a bibliography of major film directors, Italian cinema sources, reference…
Abstract
Looks at the first 100 years of Italian cinema examining its role in Italy’s recent history. Provides a bibliography of major film directors, Italian cinema sources, reference works, histories, themes, theory and criticism and articles in journals.
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Houzhe Zhang, Defeng Gu, Xiaojun Duan, Kai Shao and Chunbo Wei
The purpose of this paper is to focus on the performance of three typical nonlinear least-squares estimation algorithms in atmospheric density model calibration.
Abstract
Purpose
The purpose of this paper is to focus on the performance of three typical nonlinear least-squares estimation algorithms in atmospheric density model calibration.
Design/methodology/approach
The error of Jacchia-Roberts atmospheric density model is expressed as an objective function about temperature parameters. The estimation of parameter corrections is a typical nonlinear least-squares problem. Three algorithms for nonlinear least-squares problems, Gauss–Newton (G-N), damped Gauss–Newton (damped G-N) and Levenberg–Marquardt (L-M) algorithms, are adopted to estimate temperature parameter corrections of Jacchia-Roberts for model calibration.
Findings
The results show that G-N algorithm is not convergent at some sampling points. The main reason is the nonlinear relationship between Jacchia-Roberts and its temperature parameters. Damped G-N and L-M algorithms are both convergent at all sampling points. G-N, damped G-N and L-M algorithms reduce the root mean square error of Jacchia-Roberts from 20.4% to 9.3%, 9.4% and 9.4%, respectively. The average iterations of G-N, damped G-N and L-M algorithms are 3.0, 2.8 and 2.9, respectively.
Practical implications
This study is expected to provide a guidance for the selection of nonlinear least-squares estimation methods in atmospheric density model calibration.
Originality/value
The study analyses the performance of three typical nonlinear least-squares estimation methods in the calibration of atmospheric density model. The non-convergent phenomenon of G-N algorithm is discovered and explained. Damped G-N and L-M algorithms are more suitable for the nonlinear least-squares problems in model calibration than G-N algorithm and the first two algorithms have slightly fewer iterations.
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Francesco Schiavone, Maria Cristina Pietronudo, Annamaria Sabetta and Marco Ferretti
Total quality management is a valuable approach to continuously improve the quality of organizations; however, scholars debate its applicability to services, which require…
Abstract
Purpose
Total quality management is a valuable approach to continuously improve the quality of organizations; however, scholars debate its applicability to services, which require specific best practices that are different from those related to manufacturing. Moreover, digitization is pervading all kinds of services, but little has been written about total quality service practices in digital-based companies. For this purpose, the authors provide a holistic model of total quality service that reflects the peculiarities of such companies, guided by the question: how do total quality service practices change in digital-based service organizations?
Design/methodology/approach
The authors conduct an illustrative case study on Healthware Group, a global integrated digital health organization, to evaluate theoretical assumptions about total quality service practices in the digital environment.
Findings
The findings allow to validate the model provided. In addition, the study enables them to observe the changes the authors are witnessing in service provision in the digital era and the consequent transformation of best practices. To be accurate, the authors cannot refer to a full transformation in digital-based companies but rather to the enrichment and extension of TQS practices. The best illustration of these conclusions has been summarized in a set of propositions corresponding to seven of the key levers of a TQS model.
Originality/value
The paper represents the first attempt to discuss the relationship between total quality service and digitalization, offering a set of propositions for academics and insights for practitioners. The model can be used as a tool to visualize the different levers that successful implementation of TQS in digital-based services companies can rely on.
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Maryana Scoralick De Almeida Tavares, Cláudia Fabiana Gohr, Sandra Morioka and Thereza Rakel da Cunha
This paper aims to map literature about innovation capabilities (IC) taking into consideration industrial clusters to propose a conceptual framework that synthetizes the main…
Abstract
Purpose
This paper aims to map literature about innovation capabilities (IC) taking into consideration industrial clusters to propose a conceptual framework that synthetizes the main factors and subfactors responsible for ICs; in addition, the paper also proposes a research agenda.
Design/methodology/approach
A systematic literature review (SLR) was performed; academic papers were analyzed qualitatively and quantitatively.
Findings
The authors provide a descriptive analysis followed by a thematic synthesis, in which we present 05 enablers and 20 critical factors (CF) of IC in clusters. The proposed framework emphasizes what needs to be done or improved to increase IC in cluster-based companies. Based on this systematic review and the framework proposed, the authors identified opportunities for future research.
Research limitations/implications
The enablers and CF identified through SLR were not validated empirically. Therefore, future studies on the current topic are required to validate the framework by investigating which factors are more relevant to cluster-based companies that intend to improve their innovative performance.
Practical implications
The present findings have important implications for the identification of the factors and subfactors that may contribute to the development of IC, which may help managers and decision-makers in recognizing which factors are the most responsible for business innovation.
Originality/value
The paper identifies enablers related to the development of IC in industrial cluster and presents a research agenda. The framework represents a guideline for companies to achieve better innovation performance.
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Cristian Geldes, Jorge Heredia, Christian Felzensztein and Marcos Mora
This paper aims to use the proximity approach of economic geography with its spatial dimension (geographic) and their non-spatial dimensions (social, institutional, cognitive and…
Abstract
Purpose
This paper aims to use the proximity approach of economic geography with its spatial dimension (geographic) and their non-spatial dimensions (social, institutional, cognitive and organizational) to shed light on the determinants of business cooperation with other organizations. It is also examined whetherthis cooperation is a determining factor for business innovation (innovation networks), drawing a distinction between technological and non-technological innovations.
Design/methodology/approach
The study has a quantitative approach; it analyzes the case of 312 companies in a cluster of agribusinesses in an emerging economy (Chile). The proposal model and its interrelations are tested with exploratory factor analysis, confirmatory factor analysis and structural equation modeling.
Findings
The results show that cognitive-organizational proximity is a positive determinant of business cooperation with other organizations, whereas social and institutional proximity are negative determinants. It is also established that business cooperation is a positive determinant of business innovation. It is more relevant in the case of technological innovation unlike non-technological innovations. In addition, it is noted that business cooperation levels are lower in micro-enterprises, a result that differs from developed countries.
Practical implications
For business managers, it is best to cooperate with companies that are similar in terms of cognitive and organizational levels for innovation. At the same time, it is necessary develop strategies to reduce the social and institutional barriers to cooperation, especially in the agribusiness sector.
Originality/value
The contributions of the study are as follows: an in-depth quantitative examination of the relationships of various non-spatial proximities as determinants of business cooperation; an analysis of whether business cooperation with other organizations is a determining factor for business innovation, distinguishing between technological and non-technological innovation; and testing these relationships in the context of agribusiness in an emerging economy such as Chile’s because most of studies are related to high-tech sector and developed economies.
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Emma Su and Joshua Daspit
The literature related to knowledge management (KM) is robust with respect to insights regarding firms in general. However, less is known about the KM of family firms despite…
Abstract
Purpose
The literature related to knowledge management (KM) is robust with respect to insights regarding firms in general. However, less is known about the KM of family firms despite these firms being the most common form of business organization worldwide. Further, even though the number of studies examining family-firm KM has increased in recent years, the insights gained remain fragmented. Therefore, the purpose of this study is to help coalesce and advance the study of family-firm KM.
Design/methodology/approach
In pursuit of these goals, a systematic literature review was conducted. Using a 6-step, systematic literature review protocol, 74 articles focused on family-firm KM published in 23 journals were identified and reviewed.
Findings
This literature review contributes to the synthesis and advancement of family-firm KM scholarship in several ways. First, key factors and relationships are identified and integrated into a robust framework. Second, scholarly insights are synthesized, and a review of the primary antecedents, outcomes and moderating factors associated with family-firm KM processes is presented. Third, promising opportunities for future research are highlighted to advance family-firm KM scholarship.
Originality/value
With a focus on reducing the fragmentation in the literature, this review synthesizes insights related to the most commonly studied antecedents, outcomes and moderators associated with family-firm KM. Additionally, antecedents are organized and reviewed according to the nature of their influence on family-firm KM processes, highlighting the simultaneous opposite effects of some influences. Further, key outcomes are synthesized based on their family versus firm-centric orientation. Even further, insights and opportunities focused on advancing the theory, antecedents, outcomes, moderators and other issues related to family-firm KM are presented in an effort to support the continued progress of scholarship in this area.
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Jialin Song, Yiyi Su, Taoyong Su and Luyu Wang
The purpose of this paper is, from a resource accumulation and resource allocation perspective, to examine the variant effects of government subsidies among firms with varying…
Abstract
Purpose
The purpose of this paper is, from a resource accumulation and resource allocation perspective, to examine the variant effects of government subsidies among firms with varying levels of market power and to test how industry competition moderates the relationship between market power and allocative efficiency of government subsidies.
Design/methodology/approach
This study explores the relationship between government subsidies and firm performance from a resource-based view. The authors study the moderating role of market power and three-way interaction between subsidy, market power and industry competition on firm performance. The authors test their hypotheses using a sample of Chinese A-share manufacturing firms from 2006–2019. The authors apply firm-level panel data regressions and conduct a series of robustness tests. The marginal effect of market power and industry competition is explored via three-way moderator effect models.
Findings
This study finds that government subsidies are negatively related to firm performance. Market power, on average, strengthens the negative effect of government subsidies on performance, but such a reinforcement effect is neutralized when industry competition is intense. Government subsidies are least efficiently used when firms have market power and industry competition is low. In addition, the authors use different forms of firm performance and a various of robustness tests to verify their assumptions.
Originality/value
This paper contributes to the literature as follows. First, the authors look into subsidy–performance problem from the perspective of the resource-based view and contribute to explaining and mitigating the divergence of current findings on the subsidy–performance relationship. Second, the authors introduce market power and industry competition as moderators to study how resource allocative efficiency affects the subsidy–performance relationship. Third, the authors propose that managerial incentives have played an important role in the allocation of government subsidies, which enriches management practices.
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