bluuebunny/crossref_metadata_2025_split huggingface dataset:
Political embeddedness and multi-layered interaction effects on the performance of private enterprises: lessons from China
Authors: Gimmon Eli , Teng Ying , He Xiaobin 
Published: July 2021

PurposeThis study aims to present multi-layered embeddedness and explore the main and interaction effects of political embeddedness on the performance of private enterprises in China. This study tests multi-layered embeddedness through interaction effects between three layers, namely, political, territorial and inter-firm embeddedness. Political embeddedness is related at the personal and the firm levels.Design/methodology/approachThe authors used secondary data of four non-panel waves (2002, 2008, 2010 and 2016) of large samples having identical questions based on the Chinese private enterprises’ survey. The accumulated number of business owners’ responses is a total of 10,686.FindingsThe main effects of each of the layers of embeddedness showed a positive influence on enterprise performance consistently and unchanged over time which fits the Chinese Guanxi regardless of the immense macro-economic transition. However, unexpectedly some interactions showed negative significant effects on performance.Practical implicationsFirst, business owners should be aware of the specific contribution to the performance of political embeddedness at both the firm level and the personal level. Second, the pursuit of exercising simultaneously several layers of embeddedness may be detrimental to company performance. This study provides generalizable lessons regarding different embeddedness layers beyond the context of China’s transition economy.Originality/valueFirst, the authors extend political embeddedness to the firm level whilst in previous research this construct had been mostly related to the personal level. Second, building on the resource-based view and redundant resources the authors present the disadvantage of “over-embeddedness” as related to multi-layered embeddedness which has been understudied.
Striving for inclusion: evidence from China using a latent profile approach
Authors: Qu Jiaojiao , Zhao Shuming , Zhao Yixuan 
Published: July 2021

Purpose
This study aims to identify profiles of inclusion in the workplace to provide evidence-based guidance to build an inclusive organization.

Design/methodology/approach
Latent profile analysis (LPA), a person-centred classification analytical tool, was applied to determine the subtypes of inclusion with Mplus 7.4, using two-wave data collected from 368 employees in 8 Chinese companies.

Findings
Three subgroups were identified: identity inclusion group (the highest level of inclusion, 34.0%), value inclusion group (the moderate level of inclusion, 47.5%) and low inclusion group (the lowest level of inclusion, 18.5%). The findings indicate that groups with male, aged and highly educated members, as well as members from developed areas generally tend to feel more included and greater inclusion relates to more favourable outcomes and fewer detrimental consequences.

Research limitations/implications
As this study was conducted only in China, the results may not be generalizable to non-Chinese contexts.

Practical implications
The results may help organizational leaders develop a deeper understanding of the significance and the crux of inclusion. To address the duality of workforce diversity, managers can take initiatives to create an inclusive organization. To achieve inclusion, managers should pay attention to ways of improving the perceptions of inclusion among all employees.

Originality/value
This is among the first studies to identify the variants in inclusion in China using LPA. It reveals the subtypes and characteristics of inclusion and can serve as a starting point to explore how to realize organizational inclusion in theory and practice.
The route problem of multimodal transportation with timetable: stochastic multi-objective optimization model and data-driven simheuristic approach
Authors: Peng Yong , Luo Yi Juan , Jiang Pei , Yong Peng Cheng 
Published: July 2021

PurposeDistribution of long-haul goods could be managed via multimodal transportation networks where decision-maker has to consider these factors including the uncertainty of transportation time and cost, the timetable limitation of selected modes and the storage cost incurred in advance or delay arriving of the goods. Considering the above factors comprehensively, this paper establishes a multimodal multi-objective route optimization model which aims to minimize total transportation duration and cost. This study could be used as a reference for decision-maker to transportation plans.Design/methodology/approachMonte Carlo (MC) simulation is introduced to deal with transportation uncertainty and the NSGA-II algorithm with an external archival elite retention strategy is designed. An efficient transformation method based on data-drive to overcome the high time-consuming problem brought by MC simulation. Other contribution of this study is developed a scheme risk assessment method for the non-absolutely optimal Pareto frontier solution set obtained by the NSGA-II algorithm.FindingsNumerical examples verify the effectiveness of the proposed algorithm as it is able to find a high-quality solution and the risk assessment method proposed in this paper can provide support for the route decision.Originality/valueThe impact of timetable on transportation duration is analyzed and making a detailed description in the mathematical model. The uncertain transportation duration and cost are represented by random number that obeys a certain distribution and designed NSGA-II with MC simulation to solve the proposed problem. The data-driven strategy is adopted to reduce the computational time caused by the combination of evolutionary algorithm and MC simulation. The elite retention strategy with external archiving is created to improve the quality of solutions. A risk assessment approach is proposed for the solution scheme and in the numerical simulation experiment.
Prospect of lean practices towards construction supply chain management trends
Authors: Le Phuoc Luong , Nguyen Nguyen Thi Duc 
Published: July 2021

Purpose
To deal with the present situation and recover after the COVID-19 pandemic, construction firms are required to recognise the trends in construction supply chain management (CSCM) for the upcoming years and determine the appropriate practices towards the trends for the improvement of construction activities in terms of strategy, tactic and operations. This paper aims to recognise key trends in CSCM and uses these trends as strategic criteria for the evaluation and prioritisation of lean construction (LC) tools at different project phases including design and architectural engineering, planning and control, on-site construction and safety management.

Design/methodology/approach
The integrated analytic hierarchy process–Delphi method is used to collect and analyse the data from construction experts to evaluate the importance levels of the CSCM trends and recommend the appropriate tools for LC practices to improve project performances.

Findings
Seven key CSCM trends are identified: lean supply chain management (SCM), supply chain (SC) integration, SC standardisation, SC problem-solving, SC information-sharing, SC flexibility and SC sustainability. Based on these trends, a set of prioritised lean tools are suggested for LC practices, in which “virtual design construction” (VDC) and “last planner system” are considered as the central tools. These two LC practices can be integrated with other effective tools to support the strategic, tactical and operational targets in construction supply chain (CSC) projects.

Research limitations/implications
This study gives the managerial implications by developing an application framework of LC practices for CSC projects. The framework promotes “VDC” as a strategic tool for the phase of design and architectural engineering and considers “last planner system” as the central LC practice for the phase of project planning and control. The framework also focuses on the improvement of efficiency in construction operations by taking into account the aspects of on-site collaboration, problem-solving, improvement and safety.

Originality/value
Up to date, there is still a lack of researches in classifying and prioritising the significant LC tools for each project phase to deal with CSC issues in both breadth and depth. Thus, this study is performed to provide construction managers with the awareness of CSCM trends on which they can focus to have strategic criteria for selecting LC practices to improve CSC performances.
A cloud-edge-terminal-based robotic system for airport runway inspection
Authors: Gui Zhongcheng , Zhong Xinran , Wang Yuchen , Xiao Tangjie , Deng Yongjun , Yang Hui , Yang Rui 
Published: July 2021

Purpose
This paper aims to present a novel robotic system for airport pavement inspection tasks.

Design/methodology/approach
The cloud-edge-terminal-based distributed architecture is designed for the proposed robotic system. Then, the following three major parts are designed and deployed, respectively: Terminal: the wheeled-robot-based data collection system. Edge: remote monitoring and data analysis system. Cloud: shared database center of the inspection data and knowledge.

Findings
Validation and application results show that the proposed system satisfies the demands of automated airport pavement inspection tasks and saves the cost of manpower and time.

Originality/value
The proposed system provides a novel solution for the full process of airport pavement inspection. Compared with the traditional manual method, the robotic system can guarantee complete coverage and provide high-precision pavement inspection results with less time and labor costs.
Psychopathic Processing and Personality Assessment (PAPA): exploring factor structure
Authors: Lewis Michael , Ireland Jane , Ireland Carol , Derefaka Gail , McNeill Kimberley , Birch Philip 
Published: July 2021

Purpose
This paper aims to assess whether the factor structure of the Psychopathic Processing and Personality Assessment (PAPA) could be confirmed in a large community sample (n = 1,850), comprising three subsamples of adult men (n = 189, 248 and 198) and women (n = 499, 469 and 247). It was predicted that the four-factor solution originally proposed in earlier studies (i.e. dissocial tendencies, emotional detachment, disregard for others, lack of sensitivity to emotion) would be replicated and produce a multi-dimensional structure consistent across sex.

Design/methodology/approach
This study explored the structure of the newly developed PAPA among a non-forensic sample.

Findings
Although exploratory analysis indicated a four-factor solution, the structure was different with “lack of sensitivity to emotion” being replaced by “responsiveness to perceived aggression.” Confirmatory analyses supported this structure among women, yet a three-factor structure was preferred for men that excluded emotional detachment.

Research limitations/implications
This study highlights the importance of attending to sex differences when assessing for psychopathy.

Originality/value
This is the first confirmatory factor analysis completed on the PAPA, with the findings conveying its value when assessing for psychopathic traits among a community sample.
A two-phase decision-making model for product development based on a product-oriented knowledge inventory model
Authors: Sadeghi Dastaki Mohsen , Afrazeh Abbas , Mahootchi Masoud 
Published: July 2021

Purpose
Over the past years, many studies have explored the role of knowledge management (KM) in companies. KM is concerned with the measurement of knowledge to manage knowledge efficiently. On the other hand, the intangible nature of knowledge makes its measurement challenging. Furthermore, there is no standardized method to measure knowledge, and it is chiefly measured based on the subjective judgment of researchers. Moreover, New Product Development (NPD) departments in many companies strive to assess their knowledge in terms of company products and knowledge workers. Hence, this study aims to propose a product-based two-phase technique that measures the company knowledge inventory.

Design/methodology/approach
In the first phase, the value of knowledge is quantified relative to products, knowledge workers and the entire company using two concepts of knowledge width and depth. Then, a three-dimensional knowledge asset map (knowledge, products and knowledge worker dimensions) is designed to assess and audit knowledge workers. Finally, this technique recruits an integer linear programming model with a cost minimization objective function to optimize the supply of NPD knowledge requirements in the second phase.

Findings
This model enables managers to determine what type of knowledge can be supplied by existing knowledge workers, whether within the company or by other external sources.

Originality/value
Among existing knowledge measurement methods, only a few use a product-based measuring technique. However, they fail to offer suitable scenarios for managers' decision-making process and consider cost structures in measurement techniques. Hence, this paper attempts to overcome these drawbacks.
Ambidextrous leadership and organizational innovation: the importance of knowledge search and strategic flexibility
Authors: Jia Ruiqian , Hu Wenan , LI Shuwen 
Published: July 2021

PurposeThe purpose of this study is to examine the potential process through which leadership exerts impacts on organizational innovation. A thorough analysis was conducted by highlighting the contribution of ambidextrous leadership to organizational innovation.Design/methodology/approachData were collected from companies located in mainland China. A total of 200 cases were included in the final sample. Hierarchical regression analysis was adopted to test the hypotheses in this study.FindingsThe results showed that exploitation knowledge search and exploration knowledge search partly mediated the relationship between ambidextrous leadership and organizational innovation, respectively. Strategic flexibility could positively moderate the relationship between exploitation knowledge search and organizational innovation and had no significant impacts on moderating the relationship between exploration knowledge search and organizational innovation.Research limitations/implicationsIn this study, not only were managers provided with a sophisticated understanding of how and when ambidextrous leadership could influence organizational innovation but also concrete strategies were given for enhancing organizational innovation.Originality/valueIn this study, the interaction among ambidextrous leadership, knowledge search and organizational innovation were elucidated and the moderating impacts of strategic flexibility on the relationship between knowledge search and organizational innovation were explored. The findings of this study enriched the literature on leadership, knowledge management and innovation.
COVID-19 and the daily rate of return of three major industry sector stock price indices related to real estate
Authors: Min Hyesook , Shin Seungwoo , Taltavull de La Paz Paloma 
Published: July 2021

PurposeThis paper analyzes how three major industrial stock indices related to South Korean real estate industries are affected by the exogenous shock of the measures taken to control COVID-19, coupled with investor sentiment, which has global impacts.Design/methodology/approachThe paper uses daily stock market indices on three major stock price indices: construction industry sector index, real estate operating company (REOC) industry index and the real estate investment trust (REIT) industry index of the Korea Stock Exchange (KRX), from January 8, 2020, when the World Health Organization (WHO) began to issue official indicators regarding COVID-19, to March 27, 2020, the last trading day of the week during which the South Korean government's stock market stabilisation fund was launched.FindingsResults indicate the REIT sector's stock rate of return to be relatively less sensitive to impacts of COVID-19 compared to those of the two other indices. Impulse response analysis also shows similar results. Impulse response estimations indicate that earlier information of REITs has prominent significance in explaining changes in the time series process itself. Similar to findings of prior studies that have been conducted with long-term perspectives, results of our short-term study indicate that the medium-risk, medium-return characteristic of the real estate industry has significance even in short-term perspectives.Practical implicationsREITs can be an investment vehicle that provides strong benefits of diversified investment for mutual fund investment managers even in the case of short-term exogenous market disruptions.Originality/valueThe analysis run in the empirical exercise is the first to consider the sensibility between international stock exchanges to the effects of measures taken to control COVID-19 impact.
AI-enabled digital identity – inputs for stakeholders and policymakers
Authors: Mir Umar , Kar Arpan Kumar , Gupta Manmohan Prasad 
Published: July 2021

Purpose
This conceptual article’s primary aim is to identify the significant stakeholders of the digital identity system (DIS) and then highlight the impact of artificial intelligence (AI) on each of the identified stakeholders. It also recommends vital points that could be considered by policymakers while developing technology-related policies for effective DIS.

Design/methodology/approach
This article uses stakeholder methodology and design theory (DT) as a primary theoretical lens along with the innovation diffusion theory (IDT) as a sub-theory. This article is based on the analysis of existing literature that mainly comprises academic literature, official reports, white papers and publicly available domain experts’ interviews.

Findings
The study identified six significant stakeholders, i.e. government, citizens, infrastructure providers, identity providers (IdP), judiciary and relying parties (RPs) of the DIS from the secondary data. Also, the role of IdP becomes insignificant in the context of AI-enabled digital identity systems (AIeDIS). The findings depict that AIeDIS can positively impact the DIS stakeholders by solving a range of problems such as identity theft, unauthorised access and credential misuse, and will also open a possibility of new ways to empower all the stakeholders.

Research limitations/implications
The study is based on secondary data and has considered DIS stakeholders from a generic perspective. Incorporating expert opinion and empirical validation of the hypothesis could derive more specific and context-aware insights.

Practical implications
The study could facilitate stakeholders to enrich further their understanding and significance of developing sustainable and future-ready DIS by highlighting the impact of AI on the digital identity ecosystem.

Originality/value
To the best of the authors’ knowledge, this article is the first of its kind that has used stakeholder theory, DT and IDT to explain the design and developmental phenomenon of AIeDIS. A list of six significant stakeholders of DIS, i.e. government, citizens, infrastructure providers, IdP, judiciary and RP, is identified through comprehensive literature analysis.
Destination governance in times of change: a complex adaptive systems perspective to improve tourism destination development
Authors: Hartman Stefan 
Published: July 2021

PurposeThis paper brings together the literature on theories of complexity adaptive systems (CAS), develops an analytical framework, applies this framework to the development of tourism destinations and critically reflects on the use of this perspective.Design/methodology/approachThis paper elaborates on a CAS perspective on destination development, to further develop complexity thinking in tourism studies. This approach enables to identify policy avenues geared towards improving destination governance and contributing to sustainable tourism development.FindingsTheories of CAS offer an analytical lens to better understand destination development, drawing explicit attention to (1) the levels of the individual, (emergent) structures, the structure-agency interface and the system level, (2) the steps related to the process of adaptation that is critical for systems to survive and thrive in times of change and (3) the undervalued importance of considering the factor of time.Originality/valueApplying CAS theories help to address a range of (policy) avenues to improve destination governance, contributing to a shift in focus from reactively fixing problems to proactively addressing the structural issue of adaptive capacity building. It shows that managing tourism destination as complex systems involves a set of conditions that are critical as well as difficult to meet in tourism practice.
An averaging approach to individual time series employing econometric models: a case study on NN5 ATM transactions data
Authors: Cedolin Michele , Erol Genevois Mujde 
Published: July 2021

PurposeThe research objective is to increase the computational efficiency of the automated teller machine (ATM) cash demand forecasting problem. It proposes a practical decision-making process that uses aggregated time series of a bank's ATM network. The purpose is to decrease ATM numbers that will be forecasted by individual models, by finding the machines’ cluster where the forecasting results of the aggregated series are appropriate to use.Design/methodology/approachA comparative statistical forecasting approach is proposed in order to reduce the calculation complexity of an ATM network by using the NN5 competition data set. Integrated autoregressive moving average (ARIMA) and its seasonal version SARIMA are fitted to each time series. Then, averaged time series are introduced to simplify the forecasting process carried out for each ATM. The ATMs that are forecastable with the averaged series are identified by calculating the forecasting accuracy change in each machine.FindingsThe proposed approach is evaluated by different error metrics and is compared to the literature findings. The results show that the ATMs that have tolerable accuracy loss may be considered as a cluster and can be forecasted with a single model based on the aggregated series.Research limitations/implicationsThe research is based on the public data set. Financial institutions do not prefer to share their ATM transactions data, therefore accessible data are limited.Practical implicationsThe proposed practical approach will be beneficial for financial institutions to use, that hold an excessive number of ATMs because it reduces the computational time and resources allocated for the forecasting process.Originality/valueThis study offers an effective simplified methodology to the challenging cash demand forecasting process by introducing an aggregated time series approach.