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This paper investigates the impact of bank credit on agricultural productivity in the Central African Economic and Monetary Community (CEMAC) from 1990 to 2019. Studies’ results on the impact of bank credit on agricultural productivity are not conclusive. The studies demonstrate diverse outcomes which are debatable. The results are conflicting.

Agricultural value added (AGRVA) to the gross domestic product (GDP) proxies agricultural productivity while domestic credit to the private sector by banks (DCPSB), broad money supply, land, inflation (INF), physical capital (PHKAP) and labour supply are explanatory variables. The autoregressive distributed lag technique is utilized.

The co-integration test results show a long-run co-integration among the variables. The findings disclose that DCPSB, land and PHKAP impact positively on the AGRVA. Broad money supply, INF and labour impact negatively on the AGRVA to the GDP.

The results suggest that the CEMAC governments should encourage effective ways to increase bank credit flow to private enterprises in the agricultural sector through efficient bank's intermediation.

The governments should create more agricultural banks and improve the operation of existing ones to ensure direct credit to agricultural activities. The Bank of Central African Economic and Monetary Community should apply aggressive policy which eliminates all the bottlenecks undermining credit flow to the private sector in mutualism with agricultural productivity.

The commercial banks should give more credit to private sector to mutually benefit the agricultural sector and the banking sector. The governments of the CEMAC economies should expand funding into the capital market which considerably boosts agricultural productivity.

Studies’ results on the impact of bank credit on agricultural productivity are not conclusive. The studies demonstrate diverse outcomes which are debatable. The results are conflicting; some reveal positive impacts, some show negative impacts and others indicate U-shape behaviour. Hence, research is required to fill the lacuna.

The purpose of the paper is to develop a method to integrate the schedule-based analysis with a productivity-based analysis to prove and support the result of the damages calculation.

In this paper, a “cost and schedule impact integration” (CSI₂) model is proposed to objectively show and estimate lost productivity due to changes in construction projects.

A schedule-based analysis to include separate tracking of change order costs can be used to predict productivity due to the delay and disruption; changes in construction projects almost always result in delay and disruption. However, the schedule-based analysis needs to be integrated with a productivity-based analysis to prove and support the result of the damages calculation.

The results of this study expand upon construction practices for proving and quantifying lost productivity due to changes in construction projects.

The contribution of the paper is summarized as the introduction of a “schedule impact analysis” into a “cost impact analysis” technique to assess the damages, as well as to demonstrate the labor productivity impact due to delay and disruption in construction projects.

The study aims to empirically investigate the trends and determinants of labour productivity of the two broad sectors –industry and services – and their components, namely, manufacturing and market services sectors, in the case of major developing and developed economies of Asia-Pacific over the period 1980-2014 and make a comparison thereof.

The study uses econometric methodology of panel unit root tests, panel cointegration and group-mean full modified ordinary least squares (FMOLS).

The study finds that while capital deepening, government size, institutional quality, productivity of the other sector and financial openness affect productivity of all the sectors significantly, the impact of human capital and trade openness varies across sectors in the case of developing economies. Furthermore, the impact of technological progress becomes significant in the post-liberalization reforms period in the developing economies. The study further finds that capital deepening, human capital, government size, institutional quality, productivity of the other sector, government size and trade openness are significant determinants of productivity of all sectors of developed economies under consideration. However, the impact of technological progress is stronger for manufacturing sector than services and its components. Furthermore, while both equity and debt liabilities (as measures of financial openness) influence sectoral productivity of industry and manufacturing sectors positively and significantly in case of developed economies, only equity liabilities have a significant influence on the productivity of developing economies. This may indicate existence of more developed financial markets in the case of developed economies.

The study identifies important structural differences in determinants of productivity both across sectors and across developing and developed economies of Asia-Pacific.

Despite the great investments in information and communication technologies (ICT), research has not persuasively established corresponding productivity increases, while many studies have also found no significant relationships between productivity and ICT. However, several shortcomings have been identified in past studies, e.g. measurement errors, redistribution of impacts, ICT mismanagement. This study proposes a methodology for assessing the ICT productivity impact that overcomes these shortcomings. The methodology is tested in a dataset of three star hotels in the UK by using data envelopment analysis, a non‐parametric technique. Findings revealed that productivity gains do not accrue from ICT investments per se, but rather from the full exploitation of ICT networking and informalization capabilities. Suggestions regarding the effective and productive configuration and management of ICT applications are provided.

This paper aims to analyze the research productivity and impact of the finalists of the AIB best dissertation award, now titled the Buckley and Casson Award, but from 1987 to 2012 the Farmer Award. Specifically, this paper examines whether there is a relationship between winning the best dissertation award and subsequent publication productivity and impact. Relationships between academic institution and institutional geographic location and finalists are also examined.

The paper examines 25 years of citation counts and the number of publications in Google Scholar of Farmer Award winners and finalists of the AIB best dissertation award from inception in 1987 to 2009, with cited publications as a measure of productivity and citations as a measure of impact. Top performers in productivity and impact are identified, and the averages of winners and non-winners are analyzed in aggregate, over time and per year. Data on finalists' institution and geographic location of institution are analyzed to describe the importance of location and institution to the award.

It is found that the overall average citations of the winners of the award is less than that of the non-winners, and that in the large majority of years the non-winners have an average citation count higher than that of the winners. However, taking averages in five year increments shows more mixed results, with non-winners performing better in two periods and winners performing better in two periods, with the remaining period being split as to research productivity and impact.

Aggarwal et al. in this journal summarized a variety of data on Farmer Award finalists from the 1990s to gain insights on institutions represented by finalists, the publication record of finalists, and content of dissertations, among other characteristics. This paper updates some of the insights from that paper by examining data on award winners from 1987 to 2013, and adds further insight by examining for the first time cited publications and citation counts winners and non-winners for the same period excluding the last two years.

The aim of this article is to research on forestry green total factor productivity and explore the impact of financial support on forestry green total factor productivity.

The methods used in this study are super efficiency SBM model of undesired output and empirical model. SBM model is a kind of Data Envelopment Analysis (DEA). The SBM model with non-expected outputs (slacks-based measure) can be used to deal with the problem of efficiency measurement with multiple input and output variables and can be used to analyze the efficiency of green development of forestry economy.

First, the overall green total factor productivity of the authors’ country's forestry has shown a trend of first decline and then an increase from 2008 to 2018, and there are significant spatiotemporal differences; second, financial support has a significant positive impact on forestry green total factor productivity; third, environmental regulation has a significant threshold effect in the process of financial support on forestry green total factor productivity, and the role of financial support shows a trend of first increasing and then decreasing.

Secondly, taking the data of 30 provinces and cities in the authors’ country from 2008 to 2018 as the research object, using the super-efficiency SBM-Malmquist index to measure the country's forestry green total factor productivity and analyze its temporal and spatial changes; finally, a dynamic panel model was established to explore the impact of financial support on forestry green total factors quantitative impact on productivity, and adding environmental regulation as a threshold variable to establish a dynamic threshold regression, and found that financial support has a nonlinear impact on forestry green total factor productivity.

The inevitable change orders in construction projects have either direct or indirect impacts on a project’s duration. Reduced productivity is one of the indirect consequences that lead to major delays in the completion of the project. The purpose of this study is to develop a model that could quantify the impact of change orders on labor productivity and result in the establishment of policies to lessen their effects.

A model was developed to analyze the effects of change orders on labor productivity, then policies for managing their impacts on productivity and project duration were established. A water treatment case study was selected to serve as the scenario in which to implement and evaluate the model and policies.

The results of this study indicated that pressure to adhere to a schedule initially leads to an increase in labor productivity, but it is often followed by a significant drop that is a result of employee frustration. It was concluded that the pressure can be positive if it is applied for a short period of time; however, it continues for a significant length of time, the duration of the project will increase appreciably.

The proposed model can be implemented to identify the factors that affect labor productivity in a construction project. Its utilization will also help project managers assess when change orders occur and determine, which policies will be most effective in optimizing labor productivity.

Many attempts to justify the business value of increased investments in information technology (IT) have shown mixed results. While findings from earlier studies have been conflicting, recent firm level studies indicate that IT investments have a positive impact on productivity. However, whether IT adds value to organizations is an on going debating issue. Thus, thus it is worth of further investigation.

The paper employs multiple techniques – a regression, regression trees, and regression splines – and integrate the responses provided from each technique.

While IT investments have a positive impact on productivity, the impact is conditional and is not uniform but depends on the amounts invested in other related areas, such as non‐IT labor, non‐IT capital, and/or IT investments.

The IT impact on productivity can be maximized when investments in other related areas are considered together than when they are considered in isolation. Therefore, IT investment decisions should not be made without consideration of the levels of other investments within an organization to avoid any waste in additional investments in IT.

While most previous studies have studied in terms of its existence or non‐existence of the IT impact, we investigate the conditions under which the IT impact would or would not exist. Thus, our study provides with the opportunity for gaining a deeper understanding of the impact of IT investments on productivity.

This study examined the impact of the Input Credit Scheme (ICS) by the Integrated Water Management and Agriculture Development (IWAD) on the productivity and food security of smallholder rice farmers in Ghana.

Cross-sectional data from 250 rice farming households in the Mamprugu Moagduri district of the North East Region obtained from a multi-stage sampling technique were used for the study. Inverse Probability Weighted Regression Adjustment (IPWRA), Propensity Score Matching (PSM) and Kendall's coefficient of concordance were the methods of analysis employed.

Empirical results show that education, rice farming experience, dependency ratio, FBO membership, farm size and farm age were the significant factors influencing participation in the input credit scheme (ICS). Also, participants had an average rice productivity of 1,476.83 kg/ha, whereas non-participants had 1,131.81 kg/ha implying that participants increased their productivity by about 30%. In addition, the study revealed that participant households increased their household dietary diversity (HDDS) by 0.45 points amounting to about 8% diversity in their diets. High-interest rates associated with credit received, the short periods of credit repayment and the high cost of inputs provided under the scheme were the most challenging constraints associated with partaking in the ICS.

The available literature on agricultural interventions have predominantly emphasized input credit as a key factor for improving cropt productivity and food security of smallholders. This study provides compelling evidence that participation in ICSs can result in substantial benefits for agricultural development, as evidenced by increased productivity leading to improved food security. The significance of these findings is highlighted by the fact that, through participation in input credit schemes, smallholder rice farmers in many developing countries see substantial improvement in their capacity to access productive resources, thereby improving their productivity, while simultaneously reducing food insecurity.

Leveraging on the improved productivity of participants in the ICS, this study advocates that such input credit schemes should scale up to more food-insecure farming communities in Ghana.

The study uses a doubly robust econometric approach to evaluate the impact of ICS on smallholder rice farmers' productivity and food security in Ghana, making it the first of its kind. The findings offer a solid basis for future research and provide guidance for policymakers looking to boost agricultural development in Ghana.

The objective of the study is to analyze the impact of the adoption of the Agile Mindset on the productivity of Agile software development teams in IT enterprises during COVID-19.

A web-based survey is performed with voluntary participants working with the Agile software development professionals with a specific focus on IT enterprises around Pune, India. For this the initial exploratory literature review was performed, to explore the team's behaviors and their response to the crises like the Covid-19 pandemic. Data is collected from the targeted population using the random sampling method. A questionnaire is designed with the help of a five-point Likert scale. All the respondents were analyzed based on their behaviors shown and how adopting to Agile mindset has impacted their productivity during the pandemic. Collected data would be then analyzed using the Smart PLS-SEM methodology.

Findings of the study show that Agile software development teams adopting to Agile mindset are better at responding to crisis and quick to adapt to change as teams adopting the Agile mindset is likely to sustain or even improve their productivity during the crises like Covid-19 pandemic. Adapting to an Agile mindset is important for Agile software development teams during a crisis as a response to changes in the working as well as environmental conditions. This study also shows that by adopting an Agile mindset, development teams are better at responding to the crisis eventually improving productivity.

Research limitations for this study-scope of the study could be extended to the larger population across geographies to have improved insights Productivity Factors like- Efforts Efficiency, Backlog-management Index (BMI), and Weighted Average Productivity (VWP) for team members can be included. More behavioral factors for Agile Mindset can be considered.

Agile software development teams are characterized by collaboration and responsibility. Recent enforcement of pandemic precautionary measures has enforced Agile software development teams to work remotely and maintain social distancing while in the office. It was challenging for most of the working people to adjust to the new working conditions (Yang et al., 2021) However, in IT organizations, adopting the Agile mindset has ensured continuous software deliveries, took ownership, and quickly adapted to the volatile situations, ultimately resulting into the growth in the productivity unlike to that of other sectors of the economy.

In this study, we have analyzed the hypotheses with statistical significance in association with constructs that are in sync with the available literature. Adopting the Agile mindset values has positively impacted the team's behavior resulting in productivity improvement even in the distributed working locations in pandemic situations.

The study highlights that adopting to Agile mindset has positively impacted an Agile software development team's productivity during the Covid-19 pandemic. As environmental conditions during Covid-19 were uncertain and ambiguous and teams were working in distributed and disconnected ways, many researchers have believed that it would have affected the overall productivity. This was turned true for most of the sectors of the economy, however, Agile software development teams have shown positive trends in their productivity, as they have adopted the Agile mindset values and principles, during crises.