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This paper aims to understand whether, and if so how, the United Nations’ Sustainable Development Goals (SDGs) influence large companies’ adoption and implementation of a broader corporate purpose, beyond profit maximization.

Adopting a multiple-case study method, data were collected from semi-structured interviews with 28 managers from 16 large companies in Australia and Japan, and from secondary sources. Grounded theory methods were used to analyze the data and draw out key findings.

The study revealed the influence of the SDGs on corporate purpose depends on the SDG integration level: where and how the SDGs are integrated into management practices. The influence was more significant when the companies implemented the SDGs at a normative level compared to those implementing the SDGs at a strategic and/or operational level.

Due to the exploratory nature of the study, the sample size is limited and covers only companies in two countries. Future studies could examine the validity of the findings and the explanatory model by testing with a larger sample and expanding the scope into different countries. The study provides practical implications on how large companies’ could scale up their contributions to achieving the SDGs.

While the extant literature suggests a simple relationship between sustainability (the SDGs) and corporate purpose, this paper identified a more complex relationship. It presents in a multi-pathway model that explains the relationship, based on empirical evidence from 16 large companies in two different institutional contexts.

Knowledge-intensive public organizations (KIPOs henceforth) rely heavily on knowledge as the primary resource to provide public services. This study deals with a specific kind of KIPO in the judiciary system: the courts. The paper aims to explore the court’s managerial and organisational change resulting from the national recovery and resilience plan (NRRP) reform in response to Covid-19, focussing on how this neglected KIPO responds to change, either by showing acts of resistance or undergoing a hybridisation process.

The paper adopts a qualitative research design, developing an explorative case study to investigate the process of a court’s managerial and organisational change caused by NRRP reform and to shed light on how this neglected KIPO reacts to change, showing resistance acts and developing the hybridisation process. Thirty-one interviews in six months have been conducted with the three main actors in Courts: judges, clerks and trial clerks.

The paper shows that in this understudied KIPO, judges fiercely resist the managerial logic that decades of reforms have been trying to impose. The recent introduction of an office for speeding up trials (Ufficio Per il Processo (UPP)) was initially opposed. Then, the resistance strategy changed, and judges started to benefit from UPP delegating repetitive and low-value tasks while retaining their core activities. Clerks approached the reform with a more positive attitude, seeing in UPP the mechanism to bridge the distance between them and the judges.

Considering their relevance to society, courts must be more addressed in KIPOs' studies. This paper allows the reader to enter such KIPO and understand its peculiar features. Secondly, the article helps to understand micropractices of resistance that may hinder the effectiveness of managerial reforms.

Good abandonment behavior refers to users obtaining direct answers via search engine results pages (SERPs) without clicking any search result, which occurs commonly in mobile search. This study aims to better understand users' good abandonment behavior and perception, and then construct a good abandonment prediction model for mobile search with improved performance.

In this study, an in situ user mobile search experiment (N = 43) and a crowdsourcing survey (N = 1,379) were conducted. Good abandonment behavior was analyzed from a quantitative perspective, exploring users' search behavior characteristics from four aspects: session and query, SERPs, gestures and eye-tracking data.

Users show less engagement with SERPs in good abandonment, spending less time and using fewer gestures, and they pay more visual attention to answer-like results. It was also found that good abandonment behavior is often related to users' perceived difficulty of the searching tasks and trustworthiness in the search engine. A good abandonment prediction model in mobile search was constructed with a high accuracy (97.14%).

This study is the first to explore eye-tracking characteristics of users' good abandonment behavior in mobile search, and to explore users' perception of their good abandonment behavior. Visual attention features are introduced into good abandonment prediction in mobile search for the first time and proved to be important predictors in the proposed model.

As the world's largest emerging market, the evidence of momentum effect in China is also mixed. Meanwhile, prior studies mainly examined individual stock momentum in China, with little concern for industry momentum and its relationship with trading volume. The motivation of this study is to investigate industry momentum in China and examine whether trading volume can enhance its profitability.

Firstly, the authors test the existence of industry momentum in China; secondly, the authors test the correlation between trading volume and momentum returns using the double ranking method; finally, the authors test whether trading volume enhances the momentum returns using Fama–French five-factor model.

The authors find that there is a significant industry momentum effect in China, and the momentum returns jointly come from winner and loser portfolios. The intervals between the formation and holding periods have an impact on the performance of momentum portfolios. In terms of trading volume, the authors find that high-volume industries have industry momentum effects while low-volume industries do not. The industry momentum strategies achieve higher excess returns in high-volume industries.

Prior literature found higher momentum returns in low-volume stocks in China, but the research in this study suggests that implementing an industry momentum strategy in low-volume industries will miss out on higher returns or even bring losses, and instead the investors should invest in high-volume industries to get the best performance.

This study extends existing research by focusing on industry momentum and its relationship with trading volume in the Chinese stock market and finds an interesting relationship between industry momentum returns and trading volume, which is different from related studies.

This paper aims to examine and compare the associations between financial capability and financial anxiety (FA) before and during the coronavirus disease 2019 (COVID-19) pandemic. Specifically, financial capability is measured by three indicators: financial knowledge, financial behavior and financial confidence. This study also examines and compares the association among different income groups before and during the pandemic.

Data are from 2018 to 2021 National Financial Capability Study (NFCS). Structural equation modeling (SEM) is employed to examine the direct and indirect associations between financial capability factors and FA. Furthermore, this paper also conducts multi-group SEM for three income groups to examine the heterogeneous effects of household income.

Both before and during the pandemic, financial knowledge is directly positively and financial behavior is directly negatively associated with FA. In addition, both financial knowledge and financial behavior are positively associated with financial confidence, which in turn is negatively associated with FA. However, when taking the indirect effects into consideration, the total effects of financial capability factors on FA are all negative. Furthermore, the pandemic has intensified the negative association between financial behavior and FA rather than financial knowledge or financial confidence. Multi-group SEM shows that the positive direct effects of financial knowledge are only significant in the low-income group, while the negative direct effects of financial behavior are only significant in the low- and middle-income groups before the pandemic. However, direct effects of financial knowledge and financial behavior are significant in all income groups during the pandemic.

First, this study specifies a construct, financial confidence, to proxy perceived financial capability. Second, it examines the mediating role of financial confidence in the association between the other two financial capability factors (financial knowledge and financial behaviors) and FA. Third, it also compares the associations between financial capability factors and FA before and during the COVID-19 pandemic.

The Public–Private Partnership (PPP) modality plays an important role in the procurement of global infrastructure projects. Regarding PPP's complex transaction structure, pricing of a PPP project is critical to both parties where the government pursues a high value for money (VFM) and the investor strives to maximize its financial gains. Despite the straightforward win–win principle, a formidable compromise is often the case to end up with a fairly acceptable price, subject to many determinants such as the risk profile, expected return, technological innovation and capacities of both parties. Among them, this study chooses to examine the “managing flexibility” (MF) capacity of investors in pricing of a PPP project, in light of the widely recognized importance of a real-option perspective toward the long term, complex and uncertain PPP arrangement. This study addresses two major questions: (1) how is MF in PPP projects to be valued and (2) how are PPP projects to be priced when considering a project's MF value.

A binomial tree model is used to evaluate the MF value in PPP projects. Based on the developed MF pricing model, net present value (NPV) and adjusted VFM value are then calculated. Finally, a multi-objective decision-making method (MODM) was adopted to determine the optimal level of returns based on invested capital (ROIC), return on operation maintenance (ROOM) and concession period.

The applicability and functionality of the proposed model is investigated using a real project case. For a given return, extended NPV and adjusted VFM value were calculated and analyzed using sensitivity analysis. Factor influence is shown by the model to be dependent on factor impact on cash flow. Subsequently, a multi-objective decision-making (MODM) model was adopted to determine the optimal level of returns, where the solution approximates the real-world bidding price. Results confirm that the pricing model provides a reliable and practical PPP proposal pricing tool.

This study proposes an integrated framework for valuing MF in PPP projects and thus more accurately determine optimal pricing of PPP projects than revealed in extant research. The model offers a practical tool to aid in the valuation of PPP projects.

This study aims to explore the impact of psychosocial entitlement on workplace deviance, particularly in contexts marked by increased job autonomy. Additionally, this study delves into the organizational factors, including perceived support and justice, which play a crucial role in this dynamic.

Applying social exchange theory (SET), this study contends that fostering a fair and supportive workplace can deter entitled employees from workplace deviance. This study used time-lagged, multi-source data to analyse the interplay between psychological entitlement and workplace deviance in the presence of job autonomy and to assess the influence of perceived organizational justice and support. This study’s analysis uses SmartPLS for partial least square-structural equation modelling.

The study’s results indicate an elevated sense of entitlement among employees working autonomously and a heightened propensity for deviant behaviour when psychological entitlement increases. Yet, the data revealed moderating effects of perceived organizational support on the relationship between psychological entitlement and workplace deviance. A post hoc analysis found full mediation effects by psychological entitlement on the relationship between perceived organizational justice and workplace deviance.

To enhance organizational dynamics, management should prioritize promoting employee perceptions of organizational justice and support through impartial human resource policies, consistent policy implementation, initiatives such as virtual learning, improved mental health benefits and measurement tools for feedback on justice and support measures.

An essential theoretical contribution of this research resides in its extension beyond the conventional application of SET, traditionally associated with reciprocity in the workplace. This study showcases its effectiveness in elucidating the impact of psychosocial factors on reciprocity in organizational dynamics.

Influenced by the constantly changing manufacturing environment, no single dispatching rule (SDR) can consistently obtain better scheduling results than other rules for the dynamic job-shop scheduling problem (DJSP). Although the dynamic SDR selection classifier (DSSC) mined by traditional data-mining-based scheduling method has shown some improvement in comparison to an SDR, the enhancement is not significant since the rule selected by DSSC is still an SDR.

This paper presents a novel data-mining-based scheduling method for the DJSP with machine failure aiming at minimizing the makespan. Firstly, a scheduling priority relation model (SPRM) is constructed to determine the appropriate priority relation between two operations based on the production system state and the difference between their priority values calculated using multiple SDRs. Subsequently, a training sample acquisition mechanism based on the optimal scheduling schemes is proposed to acquire training samples for the SPRM. Furthermore, feature selection and machine learning are conducted using the genetic algorithm and extreme learning machine to mine the SPRM.

Results from numerical experiments demonstrate that the SPRM, mined by the proposed method, not only achieves better scheduling results in most manufacturing environments but also maintains a higher level of stability in diverse manufacturing environments than an SDR and the DSSC.

This paper constructs a SPRM and mines it based on data mining technologies to obtain better results than an SDR and the DSSC in various manufacturing environments.

Quality management barriers have been discovered in construction small- and medium-sized enterprises (SMEs), determining their long-term survival. Despite the recognition of Lean Six Sigma (LSS) as a valuable quality management technique for addressing the barriers faced by SMEs, LSS implementation within the construction SME context is alarmingly low. Therefore, this study aims to investigate the barriers for implementing LSS within construction SMEs and to determine the most effective strategies for overcoming these barriers.

A quantitative research approach was used, and data was collected in two stages: a questionnaire survey with 44 construction professionals and an expert opinion survey with 12 LSS specialists. The collected data was then analysed using the fuzzy TOPSIS method, achieving a higher degree of sensitivity.

The findings revealed the 15 most significant LSS barriers that need to be addressed. In addition, the ten most important strategies to be implemented in overcoming the identified barriers before LSS implementation were discovered and thematised, most notably the hiring of LSS specialists for project monitoring and the formation of a committee for strategic planning through LSS.

Previous research on LSS examined barriers and strategies for SMEs in general, but to the best of the authors’ knowledge, this study is the first of its kind, focusing especially on the construction SME context and involving the unique fuzzy TOPSIS approach.