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Change orders are a typical occurrence in building projects. Change orders indirectly affect labor productivity, resulting in a significant delay in the completion of a building project. Change orders cause labor productivity losses that are difficult to describe, establish and account for contractors and subcontractors. This study aimed to look at the influence of change orders on labor productivity and develop methods to mitigate their adverse effects.

To assess the change orders' impact on productivity levels a system dynamic model was developed and devise ways were developed to counteract these negative impacts in this research. The impact of change orders on labor productivity and project time was then controlled using techniques established. Finally, a case study of KUET's hall extension was chosen, and the model and principles developed were implemented.

This study established that if the project delivery date is set and change orders are occurring often, labor productivity will be impacted. With adequate monitoring and supplemental management techniques, it can be reduced by prolonging the project.

The developed policies aid to mitigate the effect of change orders on labor productivity.

The Islamic world spans many different languages with different language structures. This paper aims to explore one way in which language structure affects consumer response to the marketing of cobrands.

Two between subject experiments were conducted using samples of participants from Saudi Arabia and the USA. The first manipulated partner brand category similarity and brand name order, along with the structure of the language used to communicate with the market. The data for this study includes Arabic speakers in Saudi Arabia as well as English speakers in the USA. The second study explores how targeting a population fluent in multiple languages of varied structure nullifies the findings from the first study and uses Latino participants in the USA.

This study finds that when brands come from similar product categories, name order did not affect cobrand evaluations, but it did when the brands come from dissimilar product categories. Here, evaluations of the cobrand are enhanced when the invited brand is in the position that adjectives occupy in the participant’s language. The authors also find that being proficient in two languages, each with a different default order for adjectives and nouns, quashes the effect of name order otherwise seen when brands from dissimilar product categories engage in cobranding.

By examining the impact of language structure on the effects of cobrand evaluation and conducting studies among participants with differing dominant languages, this research can rule out simple primacy or recency effects.

Retailers are increasingly adding multiple platform apps. For instance, Hilton Hotel is listed on booking.com, Expedia and TripAdvisor. The purpose of this study is to examine whether and how the adoption of a second homogenous mobile platform app by new and existing consumers affects their purchasing behavior in both the original app and the overall platform apps.

With 604,864 unique data from a Chinese fast-food company, which sequentially add three food delivery platforms, this paper explores the influence of a second homogeneous mobile platform app adoption on consumer purchase frequency, order size and spending.

The results of the log-linear regression model show that multiplatform consumers are more profitable than single-platform consumers. For both existing and new consumers, multiplatform adoption would increase purchase frequency, decrease order size and increase total spending with the retailer. However, for existing consumers, multiplatform adopters are more likely to buy less frequently, spend less per order and have lower total spending in the original platform app.

This paper contributes to platform addition and multichannel literature by empirically finding that multiplatform adopters, both new and existing consumers, are more profitable than single-platform consumers. Managerially, the results suggest that companies should not hesitate to add multiple platforms and should encourage consumers to use multiple mobile apps.

First, this study examines the multiplatform addition effect on both new and existing consumers, which has not been discussed yet. Second, this study contributes to multichannel literature by finding that multiplatform consumers are more profitable than single-platform consumers. Third, unlike Rong et al. (2021), this study supports that channel capability theory is still valid in the homogenous mobile-to-mobile channel expansion context.

Digital transformation and innovation-driven development have become an international consensus. The purpose of this paper is to examine the effects of relationships, mechanisms and economic consequences between digital transformation and enterprise innovation quality in order to provide a benchmark for developing countries to implement digital transformation strategies and innovation-driven strategies and provide a major support for economic recovery in the post-coronavirus disease 2019 (COVID-19) era.

Using microdata from A-share listed enterprises in Shanghai and Shenzhen from 2010 to 2021, this study examines the relationship between digital transformation and enterprise innovation quality and further reveals the internal logic and economic consequences of digital transformation to improve enterprise innovation quality through the mediating effect and moderating effect models.

The results demonstrate that digital transformation is beneficial for improving enterprise innovation quality. The heterogeneity test demonstrates that digital transformation has a larger effect on improving enterprise innovation quality in non-state-owned enterprises and eastern enterprises in China. The mechanism test demonstrates that digital transformation can improve enterprise innovation quality by improving internal control quality and analyst attention. Furthermore, with the increase in enterprise innovation inputs, digital transformation plays a significantly stronger role in improving enterprise innovation quality. The extended analysis demonstrates that digital transformation can significantly improve enterprise financial performance by improving innovation quality.

First, the construction of the core explanatory variable digital transformation index in this study is based on the Python data analysis software, which calculates the frequency of digital transformation in the text of the business situation analysis portion of the annual report of the listed companies and then obtains the degree of digital transformation of the company in this year. There may be some deviation from the degree of digital transformation in the actual production and operation of enterprises. Second, in addition to internal control quality and analyst attention, are there other mediating mechanisms for the impact of digital transformation on the quality of enterprise innovation? Third, whether the moderating effect of innovation input on digital transformation and innovation quality is related to human capital factors of the research and development (R&D) team, such as the technical background of R&D personnel, etc.

This study enriches the relevant theories of digital transformation and broadens the research boundaries of digital transformation and enterprise innovation. This study's result provides an empirical basis for enterprises to improve enterprise innovation quality and financial performance from the perspective of digital transformation at the micro level and points out specific practical directions, combining theory with practice.

The OSCE is regarded as the gold standard of competence assessment in many healthcare programs, however, there are numerous internal and external sources of variation contributing to checklist marks. There is concern amongst organisers that candidates may be unfairly disadvantaged if they follow an “excellent” preceding candidate. This study assessed if average checklist scores differed depending on who a candidate follows accounted for different sources of variation.

This study examined assessment data from final year MBChB OSCEs at the University of Aberdeen and categorised candidates into three levels dependent on examiner awarded global scores of preceding candidates for each station. Data were modelled using a linear mixed model incorporating fixed and random effects.

A total of 349 candidates sat the OSCEs. The predicted mean (95% CI) score for students following an “excellent” candidate was 21.6 (20.6, 22.6), followed “others” was 21.5 (20.5, 22.4) and followed an “unsatisfactory” student was 22.2 (21.1, 23.3). When accounted for individual, examiner and station levels variabilities, students following an “excellent” candidate did not have different mean scores compared to those who followed “other” (p = 0.829) or “unsatisfactory” candidates (p = 0.162), however, students who followed an “unsatisfactory” student scored slightly higher on average compared to those who followed “other” (p = 0.038).

There was weak evidence that candidate's checklist variations could be attributed to who they followed, particularly those following unsatisfactory students; the difference in predicted mean scores may be of little practical relevance. Further studies with multiple centres may be warranted assuring perceived fairness of the OSCE to candidates and educators.

Although businesses continue to take up artificial intelligence (AI), concerns remain that companies are not realising the full value of their investments. The study aims to provide insights into how AI creates business value by investigating the mediating role of Business Process Management (BPM) capabilities.

The integrative model of IT Business Value was contextualised, and structural equation modelling was applied to validate the proposed serial multiple mediation model using a sample of 448 organisations based in the EU.

The results validate the proposed serial multiple mediation model according to which AI adoption increases organisational performance through decision-making and business process performance. Process automation, organisational learning and process innovation are significant complementary partial mediators, thereby shedding light on how AI creates business value.

In pursuing a complex nomological framework, multiple perspectives on realising business value from AI investments were incorporated. Several moderators presenting complementary organisational resources (e.g. culture, digital maturity, BPM maturity) could be included to identify behaviour in more complex relationships. The ethical and moral issues surrounding AI and its use could also be examined.

The provided insights can help guide organisations towards the most promising AI activities of process automation with AI-enabled decision-making, organisational learning and process innovation to yield business value.

While previous research assumed a moderated relationship, this study extends the growing literature on AI business value by empirically investigating a comprehensive nomological network that links AI adoption to organisational performance in a BPM setting.

The study aims to highlight the barriers faced by the entrepreneurs toward achieving sustainability in business and innovation cultivation by offering solutions for academicians, practitioners and policymakers. The study uses the resource-based view (RBV) theory to discuss how an organization’s resources and capabilities influence the competitive ambience and barriers faced by entrepreneurs.

The present research uses grey-causal modelling (GSC) to analyse the barriers against successful entrepreneurship.

The research focuses on the usefulness of dynamic capabilities, managing and cooperating resources in the entrepreneurship setting. The paper highlights the importance of resource gathering and nurturing as a method to combat scarcity. This research further identifies that financial limitations, regulatory obstacles, challenges to sourcing qualified labour, poor infrastructure and technology, limited mentorship opportunities, lack of scalability, low initial cost barriers in product development and risk-averse attitudes are the major factors hindering entrepreneurs from obtaining sustainable business and innovation.

The contribution of this research to the literature is that it assesses RBV theory within the realm of entrepreneurship, providing a different perspective on resources and capabilities as well as the challenges faced by entrepreneurs. The systematic approach to the analysis and prioritization of various barriers is innovative, and it adds knowledge in this area.

This study aims to provide further insights into the connection between corporate social responsibility (CSR) and companies’ credit ratings, while also exploring the role of corporate governance as a moderating factor. The hypotheses for this relationship are rooted in both legitimacy and stakeholder theories.

Using a sample of French non-financial listed firms from 2007 to 2020, this paper uses the ordered probit model introduced by Greene (2000). The issue of endogeneity has also been addressed.

The study reveals that CSR practices positively impact companies’ credit ratings by enhancing solvency and financial performance. Specifically, firms that prioritize CSR, particularly in the social and environmental dimensions (such as community relations, diversity, employee relations, environmental performance and product characteristics), tend to have higher credit ratings and a reduced risk of default. This suggests that credit rating agencies likely incorporate CSR performance when assigning credit ratings. Furthermore, the quality of corporate governance acts as a moderator, strengthening the relationship between CSR and credit ratings. The findings remain robust even after accounting for key firm attributes and addressing potential endogeneity between CSR and credit ratings.

This research provides valuable guidance for policymakers, corporate managers, investors and other stakeholders, as it offers insights into the influence of CSR activities on risk premiums and financing costs. For financial institutions, expanding credit decisions to encompass non-financial factors such as CSR can result in more accurate predictions of firm credit quality compared to relying solely on financial indicators.

To the best of the authors’ knowledge, this study stands out as the first to systematically examine the relationship between CSR and credit ratings within the French context. Moreover, it distinguishes itself by investigating the moderating influence of corporate governance on this relationship, setting it apart from prior research.

This paper aims to identify, examine, and present an empirical research design of behavioral finance of potential investors during Covid-19.

A well-structured questionnaire was designed; a survey was conducted among potential investors using convenience sampling, and 200 valid responses were collected. The research work uses multiple regression and discriminant function analysis to evaluate the influence of cognitive factors on the financial decision-making of investors.

Recency and familiarity bias are proven to have the highest significant impact on the financial decisions of investors followed by confirmation bias. Overconfidence bias had a negligible effect on the decision-making process of the respondents and found insignificant.

Covid-19 is a temporary phase that may lead to changes in financial behavior and investors’ decisions in the near future.

The paper will help academicians, scholars, analysts, practitioners, policymakers and firms dealing with capital markets to execute their job responsibilities with respect to the cognitive bias in terms of taking financial decisions.

The present investigation attempts to fill the gap in the literature on the intended topic because it is evident from literature on the chosen subject that no study has been undertaken to evaluate the impact of cognitive biases on financial behavior of investors during Covid-19.

This paper aims to investigate the mechanisms through which social media news consumption across different platforms leads to opinion polarization in society. To this end, the authors draw from cultivation theory to examine whether social media news consumption imparts a mainstreaming or resonance effect. Media consumption imparts a mainstreaming effect if frequent users, regardless of their social identity, develop homogenous attitudes about issues, whereas resonance is at play if there is a differing cultivation effect on various social groups depending on their relatability of life experiences.

The authors conduct the study in the developing context of India, using a population survey dataset from 2019. Regression-based mediation and moderation analyses were carried out to test the hypotheses.

The findings reveal that resonance is the most prominent mechanism through which social media news consumption cultivates opinion polarization, contrary to the mainstreaming effect imparted by television. Further, WhatsApp use was found to strengthen the polarizing effect of overall social media news consumption, while YouTube use weakened the cultivation of polarization.

The paper unearths how social media news consumption influences the opinion polarization of various social groups differently. The authors also find the differential effect of specific platform use. These findings have the potential to inform policymakers and developers about how to mitigate the detrimental effects of platform-based political persuasion.

This study offers significant contributions. First, the authors explain social media-induced polarization using the novel theoretical lens of cultivation. Second, the authors find that social media and television news consumption differ in their polarizing effects. Third, the authors find that while WhatsApp use amplifies the polarizing effect of social media news consumption, YouTube use weakens it.