bluuebunny/crossref_metadata_2025_split huggingface dataset:
Friction analysis of anisotropic surface for viscoelastic material
Authors: Zhao Yang , Liu Heng , Wang Nanshan , Fan Bowen , Li Meng 
Published: October 2021

Purpose
The anisotropic surfaces of viscoelastic materials play a role in sliding friction; the purpose of this paper is to study the effect of the anisotropic surfaces on contact area and the friction coefficient.

Design/methodology/approach
A complex elastic modulus and an anisotropic power spectrum are used to compute the coefficient of friction based on the extension Persson theory which considers the partial contact and the variation in the roughness slopes.

Findings
The ratios of the relative contact area that varies with velocity are obtained with different angles and eccentricities, and the effect of the elastic modulus needs to be considered. The coefficients of the friction parallel to the direction of motion decrease as the angle increases, or as the eccentricity decreases. The friction coefficients in the vertical direction change irregularly when the angles or eccentricities increase.

Originality/value
An extension of Persson’s work considering the partial contact and the effective mean square slope of the roughness is applied to study sliding friction, and the effect of the elastic modulus on contact area is considered.
Impact of COVID-19 lockdown on prices of potato and onion in metropolitan cities of India
Authors: Rajpoot Kuldeep , Singla Saurav , Singh Abhishek , Shekhar Shashi 
Published: October 2021

PurposeThis study focuses on accessing the impact of lockdown implemented to curb the pandemic of coronavirus disease 2019 (COVID-19) on prices of potato and onion crops using the time series analysis techniques.Design/methodology/approachThe present study uses secondary price series data for both crops. Along with the study of percent increase or decrease, the time series analysis techniques of autoregressive integrated moving average (ARIMA) and generalized autoregressive conditional heteroskedasticity (GARCH), as well as machine learning; neural network autoregressive (NNAR) models were used to model the prices. For the purpose of comparison, the data from past years were taken as the period of normalcy. The behaviour of the forecasts for the normal periods and during the pandemic based on respective datasets was compared.FindingsThe results show that there was an unprecedented rise in prices during the months of lockdown. It could be attributed to the decline in arrivals due to several reasons like issues with transportation and labour availability. Also, towards the end of lockdown (May 2020), the prices seemed to decrease. Such a drop could be attributed to the relaxations in lockdown and reduced demand. The study also discusses that how some unique approaches like e-marketing, localized resource development for attaining self-sufficiency and developing transport chain, especially, for agriculture could help in such a situation of emergency.Research limitations/implicationsA more extensive study could be conducted to mark the factors specifically that caused the increase in price.Originality/valueThe study clearly marks that the prices of the crops increased more than expectations using time series methods. Also, it surveys the prevailing situation through available resources to link up the reasons behind it.
Effect of women access to land on household nutritional outcomes in smallholder production system: application of heterogeneous treatment effects
Authors: kariuki Veronica Njeri , Ayuya Oscar Ingasia , Nduko John Masani 
Published: October 2021

PurposeLand is an emotive issue for women in Kenya, majority of who still suffer the consequences of not having access to land, leading to economic insecurity. This paper aims at examining the effects of women access to land on household nutritional outcomes among smallholder farmers in Kenya.Design/methodology/approachThe study uses primary data collected from a sample of 384 small-scale women farmers selected using multi-stage sampling technique. For data analysis, household nutritional outcomes were measured using Households Dietary Diversity Scores (HDDS) and Household Hunger Scale Scores (HHS). Stratification multilevel and matching-smoothing approach that controls for pre-treatment heterogeneity bias and treatment effect heterogeneity bias was used in estimating heterogeneous effects of women access to land.FindingsThe analysis reveals that women access to land has a significant positive effect on household nutritional outcomes. All households across all propensity scores strata benefited significantly but differently from women access to land in terms of nutritional outcomes.Research limitations/implicationsEconometrically, propensity matching technique used in computing heterogeneity effects captures selection bias due to observable characteristics but it fails to capture selection bias due to unobservable factors. However, robust strategies were employed to ensure minimal estimation bias.Originality/valueThe paper provides insights on the determinants of women access to land and the influence women access to land has on household nutritional outcomes. In addition, by employing one of the conventional impact evaluation techniques, the paper contributes to knowledge by taking into accounts the heterogeneity in the effects of women access to land on household nutritional outcomes.
Corporate real estate and green building: prevalence, transparency and drivers
Authors: Richter Thomas Julian , Soliva Eveline , Haase Matthias , Wrase Isabelle 
Published: October 2021

Purpose
Green building is a megatrend in corporate real estate management. This paper aims to document the prevalence of green building reporting in public firms, assess how well firms apply good practices of green building and show which firms, countries and industry sectors are particularly advanced in the application of green building technologies.

Design/methodology/approach
The study uses data on green building reporting, green building scores and firm characteristics of 1,281 publicly traded firms from different industries in Organisation for Economic Co-operation and Development countries over a 5-year period. Regression analysis is used to relate the adoption of green building reporting and excellence in green building to firm characteristics.

Findings
The results indicate that there is a huge variation in green building activities and reporting in corporate real estate management across countries and industries. The study finds that firms in the financial and health-care sectors are leading in green building reporting. Environmental, social and corporate governance-oriented, profitable and large firms receive the highest green building scores.

Research limitations/implications
The results in this paper rely on the reported but not inevitably monitored green building activities. There may also be companies that use green building technologies but do not report on them. The conclusions are largely based on correlations and do not allow for causal statements (endogenous variables).

Practical implications
The results in this paper are crucial for practitioners in corporate real estate to benchmark their green building activities and reporting. Additionally, the paper sheds light on how information on green building is propagated in the financial market.

Originality/value
The paper looks at the drivers and barriers of green building for 25 countries and across all industry sectors (1,281 firms). In contrast to that most of the existing literature focuses on single countries and limits the analysis to companies in the real estate and construction industry. Additionally, the paper has a joint focus on publicly available green building reporting and green building scores.
Failure mode, effects and criticality analysis improvement by using new criticality assessment and prioritization based approach
Authors: Chakhrit Ammar , Chennoufi Mohammed 
Published: October 2021

Purpose
This paper aims to enable the analysts of reliability and safety system to assess the criticality and prioritize failure modes perfectly to prefer actions for controlling the risks of undesirable scenarios.

Design/methodology/approach
To resolve the challenge of uncertainty and ambiguous related to the parameters, frequency, non-detection and severity considered in the traditional approach failure mode effect and criticality analysis (FMECA) for risk evaluation, the authors used fuzzy logic where these parameters are shown as members of a fuzzy set, which fuzzified by using appropriate membership functions. The adaptive neuro-fuzzy inference system process is suggested as a dynamic, intelligently chosen model to ameliorate and validate the results obtained by the fuzzy inference system and effectively predict the criticality evaluation of failure modes. A new hybrid model is proposed that combines the grey relational approach and fuzzy analytic hierarchy process to improve the exploitation of the FMECA conventional method.

Findings
This research project aims to reflect the real case study of the gas turbine system. Using this analysis allows evaluating the criticality effectively and provides an alternate prioritizing to that obtained by the conventional method. The obtained results show that the integration of two multi-criteria decision methods and incorporating their results enable to instill confidence in decision-makers regarding the criticality prioritizations of failure modes and the shortcoming concerning the lack of established rules of inference system which necessitate a lot of experience and shows the weightage or importance to the three parameters severity, detection and frequency, which are considered to have equal importance in the traditional method.

Originality/value
This paper is providing encouraging results regarding the risk evaluation and prioritizing failures mode and decision-makers guidance to refine the relevance of decision-making to reduce the probability of occurrence and the severity of the undesirable scenarios with handling different forms of ambiguity, uncertainty and divergent judgments of experts.
The role of big data for Supply Chain 4.0 in manufacturing organisations of developing countries
Authors: Narwane Vaibhav S. , Raut Rakesh D. , Yadav Vinay Surendra , Cheikhrouhou Naoufel , Narkhede Balkrishna E. , Priyadarshinee Pragati 
Published: October 2021

PurposeBig data is relevant to the supply chain, as it provides analytics tools for decision-making and business intelligence. Supply Chain 4.0 and big data are necessary for organisations to handle volatile, dynamic and global value networks. This paper aims to investigate the mediating role of “big data analytics” between Supply Chain 4.0 business performance and nine performance factors.Design/methodology/approachA two-stage hybrid model of statistical analysis and artificial neural network analysis is used for analysing the data. Data gathered from 321 responses from 40 Indian manufacturing organisations are collected for the analysis.FindingsStatistical analysis results show that performance factors of organisational and top management, sustainable procurement and sourcing, environmental, information and product delivery, operational, technical and knowledge, and collaborative planning have a significant effect on big data adoption. Furthermore, the results were given to the artificial neural network model as input and results show “information and product delivery” and “sustainable procurement and sourcing” as the two most vital predictors of big data adoption.Research limitations/implicationsThis study confirms the mediating role of big data for Supply Chain 4.0 in manufacturing organisations of developing countries. This study guides to formulate management policies and organisation vision about big data analytics.Originality/valueFor the first time, the impact of big data on Supply Chain 4.0 is discussed in the context of Indian manufacturing organisations. The proposed hybrid model intends to evaluate the mediating role of big data analytics to enhance Supply Chain 4.0 business performance.
Rethinking anti-corruption efforts in international development
Authors: Kuipers Stijn 
Published: October 2021

Purpose
Corruption is commonly seen as a primary impediment to economic development, and its eradication has therefore featured high on development agendas. Most anti-corruption efforts in international development however fail. This paper aims to review recent attempts to unpack the “black box” of corruption to better understand its functioning in developing countries and find ways to combat corruption effectively.

Design/methodology/approach
The study has been undertaken through a comparative literature and case analysis of some of the primary findings within the field of anti-corruption in international development of the past decade.

Findings
The research finds that the black-and-white conceptualisation of corruption as an impediment to economic development, which is dominant in development circles, commonly fails to understand corruption as an alternative form of problem-solving in specific institutional settings. This has both hindered anti-corruption efforts and given unwarranted primacy to anti-corruption efforts in international development, to the loss of other priorities.

Practical implications
Policy-makers need to accept that there are no “magic bullets” against corruption and work in a much more contextual manner, while accepting the fact that corruption might not be the primary impediment to economic growth in their country.

Originality/value
The paper strengthens recent calls for a more contextualized approach to combat corruption, which have been given insufficient attention in policy design and most of the literature on corruption, providing a novel starting point for “functional”, politically-aware anti-corruption and development efforts.
Corporate liability for modern slavery
Authors: Bakirci Kadriye , Ritchie Graham 
Published: October 2021

Purpose
The purpose of this paper is to provide an overview of evolving developments in international, regional and EU law including the UK and Turkish jurisdictions for the liability of corporate businesses for modern forms of exploitative labour practices described as the modern forms of slavery.

Design/methodology/approach
In the first part, this paper outlines international, regional and EU instruments, UK and Turkish jurisdictions in relation to modern forms of slavery. The second part reviews legal frameworks for corporate liability for modern forms of slavery.

Findings
Slavery, slavery-like practices or some other exploitative practices are prohibited by numerous international law instruments starting from 1904. Apart from old forms of defined exploitative practices, multiple relevant current exploitative practices, called contemporary or modern forms of slavery exist all over the world. Under various international or regional conventions signatory States have been held responsible for exploitative practices by the international or regional courts or supervisory bodies, yet businesses were largely overlooked as a participating partner in the global movement to eradicate modern forms of slavery. For many years, multi-national businesses have engaged with various voluntary international corporate social responsibility initiatives in response to demands to operate in a socially responsible manner. There is a growing global recognition of the role corporate businesses can and should play in tackling crime and exploitative practices. A number of initiatives at the international and EU level and the introduction of the California Transparency in Supply Chains Act, (2010 – effective from 2012), the UK Modern Slavery Act 2015, the French Act on Due Diligence of Corporations and Main Contractors 2017 (loi sur le devoir de vigilance), the Australian Commonwealth Modern Slavery Act 2018, the Dutch Child Labour Due Diligence Act 2019, (which is due to come into effect in mid-2022), reflect this recognition.

Originality/value
This paper argues that it is important for companies to use available tools, participate in joint initiatives and advocate for binding international and regional instruments and effective national legislation and action – all aimed at ending business involvement in modern forms of slavery.
Exploring the critical production risk factors for modular integrated construction projects
Authors: Wuni Ibrahim Yahaya , Shen Geoffrey Qiping 
Published: October 2021

Purpose
The factory production stage constitutes the bridge in the supply chains of modular integrated construction (MiC) projects. It embodies the fundamental differences between MiC and site-based construction. However, there is a poverty of knowledge of the uncertainties and risk events at the production stage. This study aims to investigate the critical production risk factors (PRFs) for MiC projects.

Design/methodology/approach
Comprehensive literature research and expert review identified and validated 22 candidate PRFs for MiC projects. A structured questionnaire survey was then used to gather opinions of domain experts in 18 countries on the relative impact of the validated PRFs for MiC projects. The collected data were analysed using multiple statistical techniques.

Findings
Statistical analysis identified nine critical PRFs for MiC projects. The top five include dimensional conflicts between modules during production; delays in production materials procurement; defective design; design information gap between designer and manufacturer; and limited capacity of manufacturers.

Originality/value
The study addressed the gap associated with identifying critical risk factors peculiar to the factory production stage of MiC projects. Its novelty lies in providing an opposite assessment of severities and prioritization of critical PRFs for MiC projects. The prioritized critical PRFs for MiC projects may inform resource allocation. Thus, it provides valuable information to MiC production specialists and project managers in their production risk planning and management strategies. The identified PRFs contribute to the theoretical checklist of MiC supply chain risk factors and may assist practitioners in assessing the severity levels of the PRFs of their MiC projects.
Non-financial performance measures and pay-performance sensitivity
Authors: Cho MyoJung , Ibrahim Salma 
Published: October 2021

PurposeThis study aims to examine whether chief executive officer (CEO) pay-performance sensitivity to shareholder wealth is related to the use of non-financial performance measures in incentive contracts.Design/methodology/approachUsing hand-collected performance measure data in a sample of S&P 500 firms across the period 1994–2010, this study investigates the sensitivity of CEO bonus and cash pay to shareholder wealth of firms that use non-financial performance (NFPM) measures of varying types and contractual weights in their bonus contracts along with financial measures (NFPM firms) in comparison to that of firms using financial measures only (FPM firms).FindingsThis study finds evidence that the pay-performance sensitivity is stronger in NFPM firms than in FPM firms. These results are driven by the use of CEO individual goals and operational efficiency. Furthermore, when using environmental, social and governance factors, the pay-performance sensitivity is stronger in terms of accounting performance only. This study also finds that using NFPM enhances pay-performance sensitivity more as their contractual weights increase and as financial risk increases.Practical implicationsThese findings are important to stakeholders, and especially regulators in understanding incentive effects of alternative performance measures. This study also sheds light on what types of non-financial measures are better in helping firms align CEOs’ incentives to shareholders’ interests.Originality/valueThis study contributes to prior research on benefits of non-financial information within the context of executive compensation. This study presents original results about the effects of contractual weights of non-financial measures and financial risk on CEO pay-performance sensitivity. This study also presents new insights regarding how different types of non-financial measures affect CEO pay-performance sensitivity.
Cyberattacks as “state of exception” reconceptualizing cybersecurity from prevention to surviving and accommodating
Authors: Knebel Sebastian , Schultz Mario D. , Seele Peter 
Published: October 2021

Purpose
This paper aims to outline how destructive communication exemplified by ransomware cyberattacks destroys the process of organization, causes a “state of exception,” and thus constitutes organization. The authors build on Agamben's state of exception and translate it into communicative constitution of organization (CCO) theory.

Design/methodology/approach
A significant increase of cyberattacks have impacted organizations in recent times and laid organizations under siege. This conceptual research builds on illustrative cases chosen by positive deviance case selection (PDCS) of ransomware attacks.

Findings
CCO theory focuses mainly on ordering characteristics of communication. The authors aim to complement this view with a perspective on destructive communication that destroys the process of organization. Based on illustrative cases, the authors conceptualize a process model of destructive CCO.

Practical implications
The authors expand thoughts about a digital “corporate immune system” to question current offensive cybersecurity strategies of deterrence and promote resilience approaches instead.

Originality/value
Informed by destructive communication of cyberattacks, this theory advancement supports arguments to include notions of disorder into CCO theory. Furthermore, the paper explains where disruptions like cyberattacks may trigger sensemaking and change to preserve stability. Finally, a novel definition of ‘destructive CCO’ is provided: Destructive Communication Constitutes Organization by disrupting and destroying its site and surface while triggering sensemaking and becoming part of sensemaking itself.
Individual knowledge measurement: organizational knowledge measured at the individual level
Authors: van den Berg Herman A. , Kaur Vaneet 
Published: October 2021

Purpose
Fundamental classifications of knowledge may be measurable as factors of production and can reveal evidence of specialization between adjacent stages of production even in the presence of shared substantive knowledge. This study of aims to distinguish between, and empirically measure, relative reliance on fundamental classifications of knowledge at the individual level.

Design/methodology/approach
In this study, investment managers were asked in an online survey to weigh their relative reliance on tacit, codified and encapsulated knowledge in executing different investment strategies for diverse client groups. Measures of relative reliance on each fundamental classification of knowledge were derived from weights assigned by each survey respondent in a series of six questions.

Findings
Survey respondents provided reliable measures of their relative reliance on tacit, codified and encapsulated knowledge. Reliance on these fundamental classifications of knowledge is shown to differ between investment managers, depending on the investment strategies being used and client groups served. These differences were exhibited notwithstanding all the respondents sharing common substantive knowledge.

Research limitations/implications
Measures of relative reliance on three classifications of knowledge were based on self-reported ratings rather than on objectively observed phenomena, making them subject to measurement error. Therefore, researchers are encouraged to observe relative reliance on tacit, codified and encapsulated knowledge in future studies.

Originality/value
The divergences in relative reliance on the fundamentally different knowledge-based factors of production were found in the presence of jointly held substantive knowledge, suggesting that fundamental classifications of knowledge are measurable and can provide evidence of specialization.