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Based on institutional theory, this study aims to analyze the influencing mechanisms of the institutional environment in the digital context on technology entrepreneurship.

Using data from the Global Entrepreneurship Monitor, World Bank and World Economic Forum, this study builds a multilevel database covering 79 countries and 97,146 individuals from 2013 to 2017. A mixed-effects logistic regression model with the fixed part and random part was chosen to test the hypotheses in this study. The mixed-effects logistic regression model used in this study includes a random intercept with random effects at the country level, while the robustness test considers a more complex two-level model with a random intercept plus random slope.

The findings indicate that different dimensions of the institutional environment in the digital context have different effects on individual technology entrepreneurship. The analysis shows that exposure to digital networks and innovative culture positively influences technology entrepreneurship. However, intellectual property rights protection has a negative impact on technology entrepreneurship. Furthermore, the government digitalization has different effects on above relationships. When a government digitalization is higher, there will be a weaker positive relationship between exposure to digital networks and technology entrepreneurship. When a government digitalization is higher, there will be a stronger positive relationship between innovative culture and technology entrepreneurship. When a government digitalization is higher, there will be a weaker negative relationship between Intellectual property rights protection and technology entrepreneurship. Finally, the effect of innovative culture on technology entrepreneurship in the digital context is stronger for females than for males.

The aforementioned findings contribute to a better understanding of the theoretical logic underlying digital factors affecting the institutional environment and technology entrepreneurship and act as a reference for the country in terms of raising its scientific and technological levels and promoting economic structure transformation in the digital era.

Facing the aging workforce but older workers’ vulnerability in the labor market, this chapter empirically explores factors and policy implications to enhance older workers’ entered employment rates (EER) after exiting the national workforce program. After reviewing older workers’ attributes and the unique methods to train them, the chapter examines demographic, socioeconomic, and program attributions to older workers’ EER, controlling for cyclical changes in the labor market. The chapter relies on three sets of models including logistic regression, multi-level mixed-effect regression, and multilevel mixed effect logistic regression models, as well as longitudinal Workforce Investment Act Standardized Record Data and Bureau of Labor Statistics unemployment data. Older dislocated workers and older adults are examined separately. Some Workforce Innovation and Opportunity Act training and related service combinations are identified to contribute to older adults and older dislocated workers’ EER and to inform strategic decision-making about future allocations of funds and policy efforts to serve older workers.

In the era of the retail Apocalypse, the surge of e-commerce has transmuted the competitive landscape for many traditional retailers that heavily rely on brick-and-mortar stores. This study examines the relationship among retail quality, market environment and businesses' survival in the context of the sporting goods retail industry.

Based on a data set from yelp.com, the authors examine the survival of 1,360 stores within 306 zip codes in the United States using mixed effects logistic modeling.

(1) Retail quality is positively related to survival, but the relationship is nonlinear; (2) the author find a null relationship between market competition and survival, which is subject to several competing interpretations; (3) 10% of the individual variation in survival is due to systematic differences between zip codes and (4) chain stores and stores with more heterogenous reviews have a higher closure rate.

This study contributes to the literature by offering an empirical testing of the relationship between retail quality and business survival and examining the impact of trading area in the modern marketing milieu. The findings have practical implications for site selection and designing a service quality program.

The purpose of this paper is to evaluate which groups of the self-employed engage in the informal economy. Until now, self-employed people participating in the informal economy have been predominantly viewed as marginalised populations such as those on a lower income and living in deprived regions (i.e. the “marginalisation thesis”). However, an alternative emergent “reinforcement thesis” conversely views the marginalised self-employed as less likely to do so. Until now, no known studies have evaluated these competing perspectives.

To do this, the author report a 2013 survey conducted across 28 countries involving 1,969 face-to-face interviews with the self-employed about their participation in the informal economy.

Using multilevel mixed-effects logistic regression analysis, the finding is that the marginalisation thesis applies when examining characteristics such as the age, marital status, tax morality, occupation and household financial circumstances of the self-employed engaged in the informal economy. However, when gender and regional variations are analysed, the reinforcement thesis is valid. When characteristics such as the urban-rural divide and educational level are analysed, no evidence is found to support either the marginalisation or reinforcement thesis.

The outcome is a call for a more nuanced understanding of the marginalisation thesis that the self-employed participating in the informal economy are largely marginalised populations.

This is the first extensive evaluation of which self-employed groups participate in the informal economy.

The purpose of this paper is to evaluate who engages in informal work. The intention in doing so is to analyse whether important causal factors of social exclusion such as age, education, gender and employment status influence participation in informal work in the European Union.

To do this, a 2013 Eurobarometer survey of who participates in undeclared work in 28 European member states is reported.

Using multilevel mixed-effects logistic regression analysis, the finding is that although some marginalised groups (the unemployed, those having difficulties paying their household bills, the working class and younger age groups) are significantly more likely to participate in the informal sector, others are not (those with less formal education and living in rural areas) and yet others (women and people in deprived European regions) are significantly less likely to participate.

The outcome is a call for a nuanced and variegated understanding of the relationship between participation in the informal sector and social exclusion.

These results display the specific populations that need targeting when seeking to tackle informal work, revealing for example that the current the allocation of European funds for tackling informal work in poorer EU regions is mistaken, but that the targeting of the unemployed is not and current policy initiatives such as smoothing the transition from unemployment to self-employment worthwhile.

This is the first extensive evaluation of the relationship between participation in the informal sector and social exclusion at the level of the European Union

The purpose of this paper is to investigate the accuracy and volatility of different methods for estimating and updating hedonic valuation models.

The authors apply six estimation methods (linear least squares, robust regression, mixed-effects regression, random forests, gradient boosting and neural networks) and two updating methods (moving and extending windows). They use a large and rich data set consisting of over 123,000 single-family houses sold in Switzerland between 2005 and 2017.

The gradient boosting method yields the greatest accuracy, while the robust method provides the least volatile predictions. There is a clear trade-off across methods depending on whether the goal is to improve accuracy or avoid volatility. The choice between moving and extending windows has only a modest effect on the results.

This paper compares a range of linear and machine learning techniques in the context of moving or extending window scenarios that are used in practice but which have not been considered in prior research. The techniques include robust regression, which has not previously been used in this context. The data updating allows for analysis of the volatility in addition to the accuracy of predictions. The results should prove useful in improving hedonic models used by property tax assessors, mortgage underwriters, valuation firms and regulatory authorities.

The purpose of this paper is to analyze the relationship between social capital and subjective ranking of household economic well-being in transition countries. The current study tests whether the performance of formal institutions moderates this link.

The analyses are based on the data from the second wave of the Life in Transition Survey. The measures “generosity of welfare policy (social safety nets)” and “ability of formal institutions to control inflation” were provided by the Bertelsmann Transformation Index Project. The study uses four measures of social capital: trust in family, trust in friends and acquaintances, trust in most people and the number of support sources. To test the hypotheses, the study employs mixed-effects regression models.

The study indicates a significant positive effect of social capital on subjective household well-being. Formal institutions do not have a significant effect on subjective ranking of household well-being. The evidence on institutions as moderators rejects the substitution effect between formal institutions and social capital. Higher generosity of welfare policy institutions and higher ability of formal institutions to control inflation strengthen the positive effect of particular trust (trust in family and trust in friends and acquaintances) on subjective ranking on the ladder of social standing (subjective ranking of household well-being), which is in line with the “crowding in” theory.

The paper adds on the limited research on transition countries. The paper contributes to the discussion on “crowding in” and “crowding out” effects of formal institutions on social capital.

Improving the nutritious quality of diets for individuals and populations is a central goal of many public health advocates and intergovernmental organizations. Yet the outcome of healthy eating has been shown to systematically vary across individual-level socioeconomic lines, and across countries in different locations of the food system. We therefore assess variation in the association between eating nutritionally dense fresh fruits and vegetables and both self-rated health (SRH) and body mass index (BMI) across individual income and country locations in the food system.

We use nationally representative survey data from 31 countries drawn from the International Social Survey Programme’s 2011 Health module. We estimate the effect of the frequency of eating fresh fruits and vegetables using random-intercept, random-coefficient multilevel mixed-effects regression models.

We confirm that eating nutritionally dense fresh fruits and vegetables frequently associates with more positive health outcomes. However, this general conclusion masks substantial individual- and country-level heterogeneity. For both SRH and BMI, the largest beneficial associations are concentrated among the most affluent individuals in the most affluent countries. Moving away from either reduces the positive association of healthy eating.

Our results provide an important wrinkle for policies aimed at changing the nutritional quality of diets. Adjustments to diets without taking into account fundamental causes of socioeconomic status will likely be met with attenuated results.

We compare two important health outcomes across a wide variety of types of countries. We demonstrate that our main conclusions are only detectable when employing a flexible multilevel methodological design.

The purpose of this paper is to provide new insights into the low-leverage phenomenon by analyzing the dynamics of firms’ financing policies. The authors explore three theoretical explanations of firms’ motivations to switch among different levels of debt aversion: financial constraints, financial flexibility and financial distress.

The authors apply a multilevel mixed-effects model to a panel data sample of 9,005 US listed firms during 1987-2014. To use a multinomial ordered logit model, the authors break down the low-leverage firms into several levels of debt aversion.

The empirical analysis provides four main findings. First, there is a dynamic behavior regarding leverage policy: after five years, 39.4 per cent of initial zero debt firms remain all-equity firms, 14.2 per cent are leveraged firms and approximately 19.7 per cent still adopt a low-leverage policy. Second, greater asset volatility increases the expected likelihood that firms will be debt averse. Third, when firms grow bigger and older, they show a greater likelihood of moving toward a higher leverage level. Fourth, results derived from the investment variables of research and development, acquisitions, and capital expenditure provide strong evidence in favor of the financial flexibility hypothesis.

These findings suggest that conservative debt policy is integrated with corporate investment decisions.

This paper contributes to extant literature by emphasizing the dynamic process associated with a low-leverage policy, unlike prior studies that focus on the determinants and characteristics of low-leverage firms. It also applies an econometric methodology that is new to the field: multilevel models.

The advancement of enterprise social networks (ESNs) facilitates information sharing but also presents the challenge of managing information boundaries. This study aims to explore the factors that influence the information-control behavior of ESN users when continuously sharing information.

This study specifies the information-control behaviors in the “wall posts” channel and applies communication privacy management (CPM) theory to analyze the effects of the individual-specific factor (disposition to value information), context-specific factors (work-relatedness and information richness) and risk-benefit ratio (public benefit and public risk). Data on actual information-control behaviors extracted from ESN logs are examined using multilevel mixed-effects logistic regression analysis.

The study's findings show the direct effects of the individual-specific factor, context-specific factors and risk-benefit ratio, highlighting interactions between the individual motivation factor and ESN context factors.

This study reshapes the relationship of CPM theory boundary rules in the ESN context, extending information-control research and providing insights into ESNs' information-control practices.