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The purpose of this study is to account for a recent non-mainstream econometric approach using microdata and how it can inform research in business administration. More specifically, the paper draws from the applied microeconometric literature stances in favor of fitting Poisson regression with robust standard errors rather than the OLS linear regression of a log-transformed dependent variable. In addition, the authors point to the appropriate Stata coding and take into account the possibility of failing to check for the existence of the estimates – convergency issues – as well as being sensitive to numerical problems.

The author details the main issues with the log-linear model, drawing from the applied econometric literature in favor of estimating multiplicative models for non-count data. Then, he provides the Stata commands and illustrates the differences in the coefficient and standard errors between both OLS and Poisson models using the health expenditure dataset from the RAND Health Insurance Experiment (RHIE).

The results indicate that the use of Poisson pseudo maximum likelihood estimators yield better results that the log-linear model, as well as other alternative models, such as Tobit and two-part models.

The originality of this study lies in demonstrating an alternative microeconometric technique to deal with positive skewness of dependent variables.

This paper aims to estimate the determinants of the intensity of use of financial inclusion by households in Ghana.

Due to the reality of a household using one or more financial products or services, this study uses the generalised Poisson model applied to GLSS6 and GLSS7 data collected in 2012/2013 and 2016/2017 respectively, to estimate the determinants of the intensity of use of financial inclusion. To deepen the analysis, a multinomial probit model is also applied.

Results show that infrastructural variables such as roads, public transport and banks stimulate the intensity of financial inclusion. In addition, agricultural development characteristics such as markets and cooperatives are essential for the intensity of inclusion.

There is a need to incorporate how many services or depth of services that people use as part of the conceptualisation of financial inclusion, as this can provide more policy-relevant evidence to enhance priority setting in financial inclusion policies. Also, micro-level financial inclusion studies in agrarian economies should consider exploring agricultural development and infrastructure variables in the modelling framework. As lead to further studies, count models of financial inclusion should consider exploring cross-country analysis, the use of panel data, or other methodological approaches to provide more robust evidence.

Previous studies have not modelled financial inclusion based on a count model as a means of measuring intensity though conceptualisations highlight the fact that people use varied financial products or services. Following from this angle, to the best of the authors’ knowledge, this study provides the first attempt at analysing the underlying determinants of the number of financial products or services used by households.

Logistical facility location decisions can make a crucial difference in the success or failure of a company. Geographical Information Systems (GIS) have recently become a very popular decision support system to help deal with facility location problems. However, until recently, GIS methodologies have not been fully embraced as a way to deal with new facility location problems in business logistics. This research makes a framework for categorizing empirical facility location problems based on the intensity of the involvement of GIS methodologies in decision making. This framework was built by analyzing facility location models and GIS methodologies. The research results revealed the depth of the embracement of GIS methodologies in logistics for determining new facility location decisions. In the new facility location decisions, spatial data inputs are almost always coupled with the visualization of the problems and solutions. However, the usage of GIS capability solely (i.e. suitability analysis) for problem solving has not been embraced at the same level. In most cases, the suitability analysis is used together with special optimization models for choosing among the multiple alternatives.

While every firm is striving to embrace digital transformation (DT) to form new differentiating business capabilities, there are dark sides to such initiatives, and it is essential to acknowledge, identify and address them. The purpose of this paper is to identify and emperically demonstrate the impact of such darksides of DT. While a firm's DT effort may have many dark sides, the authors identify data breaches as the most critical one and focus on proving their impact since it can inflict significant damage to the firm.

Through the lens of paradox theory, the authors argue that the DT efforts of a firm will lead to increased risk and severity of data breaches. The authors developed a one-of-a-kind longitudinal data set by combining data from multiple sources, including 3604 brands over a 10-year period, and employed a DT performance scorecard to evaluate a firm's DT effort across four key digital selling touchpoints: site, mobile, digital marketing and social media.

The findings of this study show that a firm's DT efforts pertaining to its mobile and digital marketing platforms significantly increase the likelihood and severity of a data breach event indicating that these two channels are most vulnerable and need heightened attention from firms. Furthermore, the findings suggest that the negative repercussions of some DT initiatives may be minimized as the firm becomes more innovative. The findings can help firms re-strategize their DT efforts by promoting security and also encouraging a balanced communication strategy.

This research is one of the first to identify, recognize and empirically illustrate the downsides of a DT effort that is otherwise thought to provide only benefits.

While the value of human capital for technological innovation is well acknowledged, literature on the role of vocational training in corporate innovation is notably scarce. The purpose of this study is to assess the effect of government support for small and medium-sized enterprise (SME) competencies on Korean firms’ innovation. The author investigates SMEs’ patent applications (supported by the government to varying degrees) while accounting for firms’ market position, ownership and management structure, as well as prior changes in firms’ technologies, products, processes and other characteristics. Alternative hypotheses about management motivation – the “lazy manager”, “career concerns” and “special East Asian institutional constraints” hypotheses – are also evaluated.

Censored and count data analysis methods are used on a panel of 595 Korean firms covering 2005–2015 from the Korean Human Capital Corporate Survey, Intellectual Property Office and National Investment Commission. A regression discontinuity estimator accounts for potential endogeneity because of support for vocational training at firms.

Firms receiving training support are more innovative than firms without support, but latent effects may play a role. The regression-discontinuity model suggests that firms that succeeded only marginally in obtaining support had higher innovative output than non-recipients near the eligibility threshold.

The findings of this study establish that government support had the intended effect on SMEs’ technological capacity. This cannot be discounted as a simple crowding-out effect. The author also establishes that management–ownership separation within firms was conducive to innovation, that product competition had an inverse U-shaped effect and that management–ownership separation had a substitutable relationship with competition in overcoming managers’ effort avoidance. The findings support the “lazy manager” hypothesis over the “career concerns” and the “special East Asian institutional constraints” hypotheses.

This study investigates the effect of user fees on access and waiting time in Nigeria. For access, the effect of user fees on both preventive and curative care; and the effect of user fees on waiting time at public healthcare facilities were examined. User fees are vital for the fiscal sustainability of healthcare provision for most African economies. Its imposition could debar healthcare access by the poor while its removal can reduce quality of care and induce longer waiting time.

The wave 3 of the Nigerian General Household Survey (2015/16) data was used for users of public health facilities. Access to healthcare was modelled using utilization data in a logistic regression model while waiting time was through the Negative Binomial Regression Model (NBRM).

The analyses showed significant effects of user fees on access to both preventive and curative care and on time spent waiting to make use of healthcare services. Individuals were able to access healthcare services regardless of amounts paid. Also, there was a non-negative effect of user fee imposition on waiting time.

Nigeria should improve healthcare facilities to address the enormous demand for healthcare services when designing policy for health sector.

This paper shows that even with the imposition of user fees, healthcare facilities could still not cater for the rising healthcare needs of the populace but cautioned that its abolition may not be a preferred option.

This study evaluates the impact of government social protection interventions on households’ welfare in South Africa.

The study uses survey data comprising 393 observations and the multinomial logistic regression technique to analyse the effect of government interventions on households’ welfare. For robustness purposes, a negative binomial regression model is also estimated whose results corroborate the main results from the multinomial regression model.

The study’s findings show that government economic interventions through social protection significantly reduce the likelihood of a decrease in household income or consumption. COVID-19 grant/social relief of distress grant, unemployment insurance, tax relief and job protection and creation are all significant in sustaining household income and consumption.

The findings have policy implications for social development. Specifically, the findings support the use of government social protection as a safety net for low-income groups in South Africa.

The study presents preliminary evidence on the effectiveness of several measures used to ameliorate the COVID-19-induced recession within the South African context.

A wetland is a place of tourist attraction, and tourism values play a key role in economic development. Among various services provided by a wetland, recreational services are increasingly valuable in the tourism sector. This paper aims to unfold the potential recreational values of the Dal Lake in Jammu and Kashmir, India.

The study uses individual travel cost methods (TCMs) and assesses its impact on regional development in terms of income and employment generation. A sample of 200 tourists is selected through an on-site survey on Dal Lake, and the demand for recreational visits and its value is estimated by employing the truncated Poisson regression model (TPRM) and un-truncated Poisson regression model (UTPRM). The consumers' surplus is estimated and tourists' benefit to visiting the wetland is explored.

On average, estimated consumers' surplus per visitor is Rs 6,250 (US$96.15) and Rs 25,000 (US$384.61) from respective models. The annual total recreational value of the lake is accounted for Rs 1713m (US$ 26m). This high consumer surplus (CS) and recreational values of the lake indicate large demand for its recreational facilities.

The study is based on primary data and thus, is original. The paper has implications for the policymakers to formulate sustainable management plans for the proper use of Dal Lake and tourism development.

Strategy scholars have widely recognized the central role that narratives play in the construction of organizational identities. Moreover, storytelling is an important strategic asset that firms can leverage to inspire employees, excite investors and engage customers' attention. This chapter illustrates how advancements in computational linguistic may offer opportunities to analyze the stylistic elements that make a story more convincing. Specifically, we use a topic model to examine how narrative conventionality influences the performance of 78,758 craftsmen selling their handmade items in the digital marketplace of Etsy. Our findings provide empirical evidence that effective narratives display enough conventional features to align with audience expectations, yet preserve some uniqueness to pique audience interest. By elucidating our approach, we hope to stimulate further research at the interface of style, language and strategy.

This research explores the impacts of content-generating devices (mobile phones versus personal computers) and content features (social content and achievement content) on consumer engagement with marketer-generated content (MGC) on social media. It also examines these factors' interaction effects on consumer engagement.

The study analyzed MGC that 210 companies had posted to Sina Weibo over three years, testing the study’s proposed model with negative binomial regression analysis.

The study's results show that MGC generated via mobile phones attracts more consumer engagement than MGC generated via personal computers. MGC with more social features attracts more consumer engagement, whereas MGC with more achievement features reduces consumer engagement. The authors also found that MGC with more social features generated via mobile phones and MGC with more achievement features generated via personal computers lead to more consumer engagement due to the congruency of the construal level of psychological distance.

This research enriches the literature by exploring the effects of content-generating devices and content features on consumer engagement in the MGC context, which extends the research on consumer engagement with social media from the context of user-generated content to the MGC.