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This empirical study aims to explore how actors in specific human resource practices (HRPs) such as line managers (LMs) impact employee productivity measures in the context of financial institutions (FI) banks.

This cross-country study adopted a qualitative methodology. It employed semi-structured interviews to collect data from purposefully selected 12 business facing directors (BFDs) working in the top 10 banks in Nigeria and the UK. The data collected were analysed with the help of the trans-positional cognition approach (TPCA) phenomenological method.

The findings of a TPCA analytical process imply that in the UK and Nigeria’s FIs, the BFDs line managers’ human resources practices (LMHRPs) resulted in a highly regulated workplace, knowledge gap, service operations challenges and subjective quantitatively driven key performance indicators, considered service productivity paradoxical elements. Although the practices in the UK and Nigerian FIs had similar labels, their aggregates were underpinned by different contextual issues.

To support LMs in better understanding and managing FIs BFDs productivity measures and outcomes, we propose the Managerial Employee Productivity Operational Definition framework as part of their toolkit. This study will be helpful for banking sectors, their regulators, policymakers, other FIs’ industry stakeholders and future researchers in the field.

Within the context of the UK and Nigeria’s FIs, this study is the first attempt to understand how LMHRPs impact BFDs productivity in this manner. It confirms that LMHRPs result in service productivity paradoxical elements with perceived or lost productivity implications.

This study aims to examine the enablers of productivity of enterprise-level Agile development process using modified total interpretative structural modeling (TISM). The two main objectives of the current study are to determine the variables influencing enterprise-level agile development productivity and to develop modified TISM for the corresponding components.

To identify enablers of the productivity of enterprise-level agile software development process a literature review and opinions of domain experts were collected. A hierarchical relationship among variables that show direct and indirect influence is created using the modified TISM (M-TISM) technique with Cross Impact Matrix-Multiplication Applied to Classification analysis. This study examined and analyzed the relationships between the determinants within the enterprise using a M-TISM technique.

With the literature review, the study could identify ten enabling factors of the productivity of Agile development process at the enterprise level. Results depict that program increment (PI) planning and scalable backlog management, continuous integration and continuous delivery (CI/CD), agile release trains (ART), agile work culture, delivery excellence, lean and DevOps practices, value stream mapping (VMS), team skills and expertise, collaborative culture, agile coaching, customer engagement have an impact on the productivity of enterprise-level Agile development process. The results show that team collaboration, agile ways of working and customer engagement have a greater impact on productivity improvement for enterprise-level Agile development process.

The developed model is useful for organizations employing scaled Agile development processes in software development. This study provides a recommended listing of key enablers, that may enable productivity improvements in the Agile development process at the enterprise level. Strategists should focus on team collaboration and Agile project management. This study offers a modified TISM model to academicians to help them understand the effects of numerous variables on maintaining the productivity of an enterprise-level Agile. The identified characteristics and their hierarchical structure can help project managers during the execution of Agile projects at the enterprise level, more effectively, increasing their success and productivity.

The study addresses the gap in the literature by interpretative relationships between the identified enabling factors. The model validation is carried out by a panel of nine experts from several information technology organizations deploying Agile software development at the enterprise level. This unique method broadens the knowledge base in Agile software development at scale and provides project managers and practitioners with a practical foundation.

This study aims to examine the impact of financial inclusion and bank stability on agricultural productivity in Sub-Saharan Africa (SSA).

The study used 38 countries in the SSA with data spanning between 2004 and 2021. The data were analyzed using the two-step system generalized method of moments (GMM) and the panel-corrected standard error (PCSE) model.

The study found a positive effect of financial inclusion and bank stability on agricultural productivity. The study also discovered that while the access component of financial inclusion has a negative influence on agricultural productivity, the usage dimension has a positive impact.

The study suggests to policymakers that an inclusive and stable financial system improves agricultural productivity. The findings recommend that policymakers should empower farmers to leverage financial inclusion.

This study provides insightful discussion on the impact of financial inclusion and its various dimensions and bank stability on agricultural productivity in SSA.

Due to the rapid development of artificial intelligence (AI) technology, increasing the use of AI in healthcare is critical, but few studies have explored the extent to which physicians cooperate with AI in their work to achieve productive and innovative performance, which is a key issue in operations management (OM). We conducted empirical research to answer this question.

We developed a conceptual model based on the ambidextrous perspective. To test our model, we collected data from 200 Chinese hospitals. One senior and one junior physician from each hospital participated in this research so that we could get a more comprehensive view. Based on the sample of 400 participants and the conceptual model, we examined whether different types of AI use have distinct impacts on physicians’ productivity and innovation by conducting hierarchical regression and post hoc tests. We also introduced team psychological safety climate (TPSC) and AI technology uncertainty (AITU) as moderators to investigate this topic in further detail.

We found that augmentation AI use is positively related to overall productivity and innovative job performance, while automation AI use is negatively related to these two outcomes. Furthermore, we focused on the impacts of the ambidextrous use of AI on these two outcomes. The results highlight the positive impacts of complementary use on both outcomes and the negative impact of balance on innovative job performance. TPSC enhances the positive impacts of complementary use on productivity, whereas AITU inhibits the negative impacts of automation and balanced use on innovative job performance.

In the age of AI, organizations face greater trade-offs between performance and technology management. This study contributes to the OM literature from the perspectives of operational performance and technology management in three ways. First, it distinguishes among different AI implementations and their diverse impacts on productivity and innovative performance. Second, it identifies the different conditions under which automation AI use and augmentation are superior. Third, it extends the ambidextrous perspective by becoming an early adopter of this approach to explore the implications of different types of AI use in light of contingency factors.

Insufficient productivity development in the global and Finnish infrastructure sectors indicates that there are challenges in genuinely achieving the goals of resource efficiency and digitalization. This study adapts the approach of capability maturity model integration (CMMI) for examining the capabilities for productivity development that reveal the enablers of improving productivity in the infrastructure sector.

Civil engineering in Finland was selected as the study area, and a qualitative research approach was adopted. A novel maturity model was constructed deductively through a three-step analytical process. Previous research literature was adapted to form a framework with maturity levels and key process areas (KPAs). KPA attributes and their maturity criteria were formed through a thematic analysis of interview data from 12 semi-structured group interviews. Finally, validation and refinement of the model were performed with an expert panel.

This paper provides a novel maturity model for examining and enhancing the infrastructure sector’s maturity in productivity development. The model brings into discussion the current business logics, relevance of lifecycle-thinking, binding targets and outcomes of limited activities in the surrounding infrastructure system.

This paper provides a new approach for pursuing productivity development in the infrastructure sector by constructing a maturity model that adapts the concepts of CMMI and change management. The model and findings benefit all actors in the sector and provide an understanding of the required elements and means to achieve a more sustainable built environment and effective operations.

This study aims to examine the impact of renewable energy consumption on agricultural productivity while accounting for the effect of financial inclusion and foreign direct investment in Brazil, Russia, India, China and South Africa (BRICS) countries during 2000–2020.

The study has used the latest data from World Bank and International Monetary Fund databases. The dependent variable in the study is agricultural productivity. Renewable energy consumption, carbon emissions, financial inclusion and foreign direct investment are independent variables. Autoregressive distributed lag (ARDL) approach was used to examine the short-run and long-run impact of renewable energy consumption, carbon emissions, foreign direct investment and financial inclusion on agricultural productivity.

The findings imply that consumption of renewable energy, carbon emissions and foreign direct investment have a positive impact on agricultural productivity while financial inclusion in terms of access does not seem to have any significant impact on agricultural productivity. Providing farmers, access to financial services can be beneficial, but its usage holds more importance in impacting rural outcomes. The problem lies in the fact that there is still a gap between access and usage of financial services.

Policymakers should encourage the increase in the usage of renewable energy and become less reliant on non-renewable energy sources which will eventually help in tackling the problems associated with climate change as well as enhance agricultural productivity.

Most of the earlier studies were based on tabular analysis without any empirical base to establish the causal relationship between determinants of agricultural productivity and renewable energy consumption. These studies were also limited to a few regions. The study is one of its kind in exploring the severity of various factors that determine agricultural productivity in the context of emerging economies like BRICS while accounting for the effect of financial inclusion and foreign direct investment.

The purpose of this study is to compare the competition and productivity of the US freight rail transportation industry for the past 41 years (1980 ∼ 2020), which consists of the two periods, before and after the abolishment of the Interstate Commerce Commission (ICC) in 1995.

This study investigates any relationships between the market concentration index values and labor productivity values in the separate two periods, and how the existence of a regulatory body in the freight transportation market impacted the productivity of the freight rail transportation industry by using a Cobb–Douglas production function on annual financial statement data from the US stock exchange market.

This study found that, after the abolishment of the ICC: (1) the rail industry became less competitive, (2) even if the rail industry had an increasing labor productivity trend, there was a strong negative correlation between the market concentration index and labor productivity and (3) the rail industry’s total factor productivity was decreased.

This study is to find empirical evidence of the effect of the ICC abolishment on the competition and productivity levels in the US freight rail transportation industry using a continuous data set of 41-year financial statements, which is unique compared to previous studies.

Hoping to increase the productivity of their employees, firms provide and expect their employees to use approved mobile apps. However, despite an intuitive appeal, the relationship between information technology usage and productivity is still seen as paradoxical. This study examines the relationship between employees' experience and engagement with business mobile apps provided by employers and its effects on employee work productivity.

Data from respondents who use employer-provided business apps were used to test the hypotheses. Measurement-corrected latent scores extracted from the PLS measurement evaluation were used in regression-centric assessment using PROCESS.

Results indicate that employee-users’ experience-based attributions of the business app, i.e. customization, performance quality and compatibility, have positive effects on productivity mediated by participation intensity. Further, work type (retail vs non-retail) and the depth of the employee user’s experience moderate experience-based attributions' indirect effects on productivity.

Unlike previous studies delving into this topic, this study focuses solely on the mediation and moderation effects for hypothesis testing. Specifically, this study investigates effects conditional on work type (retail vs non-retail), which the authors believe has significant implications for retailing. These findings have interesting implications for both future research and managers.

This study investigates the moderating effect of CEO power on the relationship between labor productivity and financial performance in the Tehran Stock Exchange (TSE).

In this study, the power of the CEO variable was measured using the power index method and its effect on the relationship between labor productivity and financial performance was tested using a multivariate regression. The study sample consisted of 1,040 observations and 130 firms listed on the TSE over an eight-year period between 2012 and 2019. Panel data and appropriate statistical techniques were applied to estimate models. In this study, Tobin’s Q and return on assets (ROA) are the two variables used to measure financial performance.

The results of the hypotheses show that the link between labor productivity and financial performance based on Tobin’s Q and ROA strengthens with increasing CEO power. Thus, the stewardship theory is approved on the TSE. In addition, CEO power and labor productivity have a positive impact on firm performance.

To the best of the author’s knowledge, this is the first study to examine the moderating impact of CEO power on the relationship between labor productivity and firms' financial performance in emerging capital markets. Therefore, the results of this study can be used by investors, board of directors, policymakers and regulations.

Taking into consideration the sanctions on Iran's economy during the study period and to increase the productivity and financial performance of the company, the results of this study can provide a practical guide for the board of directors to consider the characteristics of CEO power and how to choose it in the emerging capital market. Additionally, the study results show that investors should choose companies with strong CEO to invest in the Iranian capital market.

The current study is the first study conducted in an emerging economy to examine the moderating impact of CEO power on the link between labor productivity and financial performance.

This chapter provides an empirical assessment of the effects of infrastructure provision on structural change and aggregate productivity using industrylevel data for a set of developed and developing countries over 1995–2010. A distinctive feature of the empirical strategy followed is that it allows the measurement of the resource reallocation directly attributable to infrastructure provision. To achieve this, a two-level top-down decomposition of aggregate productivity that combines and extends several strands of the literature is proposed. The empirical application reveals significant production losses attributable to misallocation of inputs across firms, especially among African countries. Also, the results show that infrastructure provision has stimulated aggregate total factor productivity growth through both within and between industry productivity gains.