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Micro, small and medium-sized enterprises (MSMEs) are the backbone of economic development for every economy. They contribute to local economic development through household wealth creation, employment generation and poverty reduction. Despite this pivotal role, MSMEs lack access to finance, and scholarship on the enabling role of financial inclusion on micro, small and medium-sized enterprises' performance is scant. The authors contribute to closing the knowledge gap by examining the enabling effect of financial inclusion on MSMEs using the FinScope MSME 2017 survey for the Kingdom of Eswatini. This paper aims to discuss the aforementioned objective.

The study used the re-centered influence function regression framework to estimate unconditional quantile regressions and the generalized ordered logit model to analyze the data.

The findings from the unconditional quantile regression revealed that small changes in access to bank accounts, saving for business, formal saving, stokvel and informal saving at the 50th and 75th percentiles have a positive and statistically significant effect on microenterprises' annual turnover profit. Conversely, small changes in formal insurance have a mixed effect on annual turnover profit. At the 10th and 25th percentiles, a small increment in insurance reduces annual turnover profit but increases microenterprise annual turnover profit at the 75th percentile. Meanwhile, the evidence from the generalized ordered logit model showed that financial inclusion reduces the likelihood of microenterprises being classified as least developed and increased the chances of microenterprises falling into emerging and developed business categories.

This study makes use of a cross-sectional survey dataset, as a result, it does not infer causal relationships over the long term, but rather an association between the independent and dependent variables.

Overall, formal and informal financial inclusion enhances the annual turnover profit for microenterprises, particularly at the 50th and 75th percentiles in the Kingdom of Eswatini. The authors recommend a specialized institution such as a micro, small and medium-sized partial credit guarantee scheme to improve the quality and affordability of credit for microenterprises, and a mix of financial and non-financial supports depending on the development stage to boost a sustainable microenterprises' sector.

The study uses two advanced cross-sectional techniques, the recentered influence function framework and the generalized ordered logit model to analyze the data. The paper is original and contributes to the discussion of the role of financial inclusion in enabling microenterprises' success in Africa, using the FinScope 2017 survey of microenterprises in Eswatini as a case study.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-10-2020-0689.

This study aims to apply the extended theory of planned behaviour (ETPB) to investigate the factors influencing the intention to give zakāt on employment income.

This study draws the required data through a survey in three main cities Makkah, Medina and Jeddah in Kingdom of Saudi Arabia (KSA). The final data sample is consisting of 650 useable questionnaires to analyse the objective of this study.

The study finds that moral norm, injunctive norm, descriptive norm and past behaviour have a significant influence on the intention to pay zakāt on employment income. The perceived behavioural control and attitude have a negative and weak impact on the intention to give zakāt on income.

The findings of this study can be useful for the policymakers and regulators to enhance peoples' awareness to give zakāt to eradicate poverty and inequality in Muslim societies. zakāt is for the deprived people, so the consequences of this study might help to improve their liveability.

This study is unique because it identified the behavioural factors that affect the peoples' intention to give zakāt in KSA have yet to be profoundly explored in the literature. This study has gathered primary data and applied the ETPB to identify the factors influencing the zakāt compliance behaviour in KSA.

The quality of voluntary sector-led community health programmes is an important concern for service users, providers and commissioners. Research on the fidelity of programme implementation offers a basis for assessing and further enhancing practice. The purpose of this paper is to report on the fidelity assessment of Living Well Taking Control (LWTC) – a voluntary sector-led, community-based education programme in England focussing on the prevention and management of type 2 diabetes.

This fidelity of implementation (FoI) study was conducted with the Devon-based LWTC programme. A fidelity checklist was developed to analyse audio records of group-based lifestyle education sessions – implementation was rated in terms of adherence to protocol and competence in delivery; the influence of wider contextual factors was also assessed. Kappa statistics (κ) were used to test for inter-rater agreement. Course satisfaction data were used as a supplementary indicator of facilitator competence.

Analysis of 28 sessions, from five diabetes prevention and two diabetes management groups (total participants, n=49), yielded an overall implementation fidelity score of 77.3 per cent for adherence (moderate inter-rater agreement, κ=0.60) and 95.1 per cent for competence (good inter-rater agreement, κ=0.71). The diabetes prevention groups consistently achieved higher adherence scores than the diabetes management groups. Facilitator competence was supported by high participant satisfaction ratings.

An appropriate level of implementation fidelity was delivered for the LWTC group-based education programme, which provides some confidence that outcomes from the programme reflected intervention effectiveness. This study demonstrates the viability of assessing the FoI in a voluntary sector-led public health initiative and the potential of this method for assuring quality and informing service development.

Using bank-level data over the 1994–2015 period, the authors aim to investigate the role of bank-specific factors on credit risk in Italy by considering two different groups of banks, namely, cooperative and non-cooperative (commercial and popular), in different local markets.

Relying on highly territorially disaggregated data at labour market areas’ level, the authors estimate the impact of the role of bank-specific factors on credit risk in Italy from the estimation of a fixed-effect estimator. Non-performing loans to total loans has been used as a proxy of credit risk; the bank-specific factors are as follows: growth of loans, reflecting credit policy; log of total assets, controlling for banks’ size; loans to total assets, reflecting the volume of credit market; equity to total assets, capturing the solvency of banks and reflecting their capital strength; return on assets, reflecting the profitability of banks; deposits to loans, reflecting the intermediation cost; cost of total assets, reflecting the banks’ efficiency or volume of intermediation cost.

The empirical findings suggest that regulatory credit policy, capitalisation, volume of credit and volume of intermediation costs are the main bank-specific factors affecting non-performing loans. Nevertheless, the present analysis suggests that the behaviour of cooperative banks’ behaviour seems to be in line with that of commercial rather than popular banks, casting doubts about the feasibility of their credit policies. It turns out that recent reforms involving popular and cooperative banks represent the first step toward the enhancement of the stability and efficiency of the Italian banking system. While the present study’s benchmark results are not particularly affected by the degree of competition in the banking sector and by banks’ size, it shows that both cooperative and non-cooperative banks have undertaken more prudent credit policies after the advent of the financial crisis and the introduction of the Basel regulation.

The relationship between bank-specific factors and credit risk has been analysed using a rich sample of cooperative, commercial and popular banks in Italy over the 1994–2015 period. The authors rely on labour market areas being sub-regional geographical areas where the bulk of the labour force lives and works. The contribution is motivated by the financial distress experienced after the 2008 financial crisis, which has significantly hit the Italian banking system and cooperative banks in particular.

In this paper, the authors study the long-run determinants of total factor productivity (TFP) in three major European economies over the period 1983–2017, namely Germany, France and Italy.

The authors focus on the capital misallocation effects, scale effects and labor misallocation effects. To this end, the authors study how real interest rate shocks, real exchange rate shocks, real wage shocks and changes in labor regulation affected TFP in major European countries over the last decades. The authors employ a theoretical and an empirical model to investigate the issue. The empirical results are obtained using a VAR model for estimation.

A stripped-down model of labor market in open economy with technology progress allows to identify the relevant variables affecting TFP. On the empirical ground, the authors find a positive relationship between TFP and real interest rate in the long run. Importantly, the authors detect a positive relationship between TFP and real exchange rate. Further, the authors show that the TFP can respond positively to a stricter labor market regulation and to a higher real compensation per employee. The results provide support to the idea that TFP has a positive relation with prices in the long run, while it may be biased along the cycle because of price rigidity.

The present model is stylized and may not capture all of the details of reality. The analysis should be extended to a larger number of countries. Technology progress could be proxied using different variables, as the R&D expenditure or the number of patents. Micro data, for specific sectors and industries, can improve the quality of the empirical investigation.

Mainly the authors find that TFP has a positive relationship with price changes in the long run, while it may be biased along the cycle because of price stickiness. Capital misallocation and labor misallocation can negatively affect TFP. Thus, the observed divergences in European TFP can be traced back to the misallocation effects attributable to the decrease of real interest rate and real wages, together with the raising labor flexibility. Mainly, the authors detect a positive long-run relationship between TFP and real exchange rate. This outcome strengthens the supply-side view of the relationship between productivity and real exchange rate.

The authors believe that the present setup can be helpful to reflect critically on the nodes at the core of the productivity slowdown and asymmetries in the eurozone. The aim is to implement renewed policies in order to favor economic growth, convergence and stability in the euro area.

This research addresses the issue of asymmetries among European economies by focusing on the role played by real prices in the long run. Traditionally, the dynamics of TFP have been attributed only to technological components, human capital and knowledge. This work shows that the dynamics of prices such as the real interest rate, the real exchange rate and the real wage can also influence the technological process by pushing the production system toward choices that are not always optimal for economic growth. An interesting result of this research concerns the positive relationship between real exchange rates and TFP in the long term, evidence of an important supply-side effect on the technological process.

The purpose of this paper is to assess the effect of financial derivatives use on different exposures by comparing domestic firms, domestic multinational corporations (MNCs) and affiliates of foreign MNCs using a unique hand-collected data set of derivatives activities from 881 non-financial firms in eight East Asian countries over the period of 2003-2013.

In this paper, the authors apply a two-stage approach. In the first stage, exposures to country risks, exchange rate and interest rate risks are estimated by using the market model. In the second stage, potential effects of firms’ derivatives use on multifaceted exposures are investigated by carrying out pooled regression model, and panel data regressions with random effect specifications.

The authors provide novel evidence that financial hedging of domestic firms and domestic MNCs reduces exposure to home country risks by 10.91 and 14.42 percent per 1 percent increase in notional derivative holdings, respectively, while affiliates of foreign MNCs fail to mitigate exposure to host country risks. The use of foreign currency and interest rate derivatives by domestic firms and domestic MNCs is effective in alleviating such firms’ exposures to varied degrees, while foreign affiliates’ use of derivatives can only lower interest rate exposures.

The primary theoretical contribution of this study is applying the market model to estimate exposures to home and host country risks. Regarding empirical contributions, the authors provide strong evidence that the use of financial derivatives by domestic firms and domestic MNCs significantly contributes to a decline in exposure to home country risks, and evidence the outperformance of domestic MNCs vis-à-vis domestic firms and foreign affiliates.

Drawing on a user-centred design perspective, the purpose of this paper is to (i) provide an overview of three contextual user research methods, namely, spatial walkthroughs, experience curve mapping and card sorting, (ii) exemplify their applications in different case studies and (iii) compare the methods according to their contributions for the study of users’ workplace experiences. Previous workplace studies with qualitative approaches mainly rely on methods such as interviews and observations. Although these methods provide rich data, the understanding of office users, their use situations and finding more fitting workplace designs can benefit from deeper user experience insights.

Three methods and their variants were tested in studies of user experience in flexible offices: spatial walkthroughs, experience curve mapping and card sorting. The methods were tested during workshops and interviews in four case studies with a total of 114 participants.

Spatial walkthroughs were more immersive and provided the most insights on the actual context with respect to spatial design qualities, while experience curve mapping enabled understanding the temporal aspects of the user experience and card sorting enabled exploring user experiences with respect to predetermined spatial qualities and contextual aspects.

Spatial walkthroughs, experience curve mapping and card sorting methods have not previously been applied in workplace studies. They facilitate dialogue, participation and user involvement and provide insights for making evidence-based recommendations for designing or redesigning office environments that fit users’ needs and preferences.

This paper considers locating congested fast charging stations (FCSs) and deploying chargers in a stochastic environment, while the related studies have predominantly focused on problems in deterministic environments. Reducing the inconvenience caused by congestion at FCSs is an important challenge for FCS service provider. This is the underlying motivation for this study to consider a problem for FCS network design with the congestion restriction in a stochastic environment. We proposed a maximal coverage problem subject to budget constraints and a congestion restriction in order to maximize the demand coverage. With the derivation of the congestion restriction in the considered stochastic environment, the problem is formulated into an integer programming model. A real-life case study is conducted and managerial implications are drawn from its results.

Minimizing the energy consumption in a wireless sensor node is important for lengthening the lifetime of a battery. Radio transmission is the most energy-consuming task in a wireless sensor node, and by compressing the sensor data in the online mode, it is possible to reduce the number of transmission periods. This study aims to demonstrate that temporal compression methods present an effective method for lengthening the lifetime of a battery-powered wireless sensor node.

In this study, the energy consumption of LoRa-based sensor node was evaluated and measured. The experiments were conducted with different LoRaWAN data rate parameters, with and without compression algorithms implemented to compress sensor data in the online mode. The effect of temporal compression algorithms on the overall energy consumption was measured.

Energy consumption was measured with different LoRaWAN spreading factors. The LoRaWAN transmission energy consumption significantly depends on the spreading factor used. The other significant factors affecting the LoRa-based sensor node energy consumption are the measurement interval and sleep mode current consumption. The results show that temporal compression algorithms are an effective method for reducing the energy consumption of a LoRa sensor node by reducing the number of LoRa transmission periods.

This paper presents with a practical case that it is possible to reduce the overall energy consumption of a wireless sensor node by compressing sensor data in online mode with simple temporal compression algorithms.

Risks are considered a significant obstacle to Green Building (GB) development and have recently received significant attention from both construction practitioners and academics. This study aimed to identify critical GB risks and explore the relationship between participants' characteristics and risk assessment.

Firstly, a list of GB risks was developed based on a comprehensive literature review and interviewing GB experts. After that, a survey of 207 construction professionals was then conducted to validate these GB risk factors. Finally, this research adopted the ANOVA test and hierarchical regression analysis to examine the relationship between participants' characteristics and risk assessment.

The results provided a list of GB risks classified and evaluated according to the GB project life cycle and, thus, may serve as a helpful reference for GB practitioners. Notably, the ANOVA analysis revealed that risk assessment negatively correlates with participants' GB experience, while their industry experience does not affect risk assessment. Furthermore, the hierarchical regression analysis proved that participant roles do not moderate the association between risk assessment and GB experience.

This study contributed to GB literature by implementing empirical research on GB risks in a developing country. The results implied the essential role of professionals with rich GB experience in risk management in GB projects. Furthermore, this research could help construction practitioners understand GB risks adequately and thereby have better risk-management strategies for future GB projects.