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Status of fiscal health of local governments helps in determining planned budget and realistic action plan for citizens’ wellbeing. This paper aims to assess the fiscal health of local governments in Bangladesh.

Using data from 18 south-western municipalities of Bangladesh during the fiscal year 2018–19, this research measures fiscal health by applying Wang, Dennis and Tu’s solvency test and Brown’s Ten-Point Test.

The result shows that one-tenth of the entire municipalities are endowed with better position, whereas almost 39 percent of municipalities are in the worst situation and nearly 50 percent of municipalities are in the average category. Because of having limited liabilities, the municipalities are endowed with more than enough cash solvency and reasonable level of long-run solvency. The key problems are that budgetary solvency of all municipalities is not satisfactory, and service expenses are more than their revenue generation. This study suggests improving the financial capabilities of the municipalities through properly using their resources, generating loans, and claiming a need-based budget from the central government.

The paper investigates the status of fiscal solvency of local governments in Bangladesh in a new dimension. The findings might be helpful to policymakers in budgeting for development initiatives of local governments in Bangladesh so that citizens’ better wellbeing is ensured.

The current study conceptualizes and empirically tests a new model of market brand equity (MBE). This model, that not just provides an understanding of customer mindsets toward the brand, as most empirical models do, but also measures the marketing benefits of such mindsets. The present study offers two models. One is comprehensive and theoretical while the other is an empirical model. The empirical model is a practical model drawn from the more comprehensive and conceptualized model. The hypothesized empirical MBE model is tested using structural equation modeling (SEM) analysis followed by a formula that offers a method to calculate and rank competitive brands in the market place. The purpose of this paper is to conclude with a discussion of the implications of the model.

The findings of the present research are based on a representative sample of 964 cellular phone users selected randomly from an Israeli internet panel were analyzed. The questions related to the dimensions of the brand equity needed a more intimate relationship of the customers with the brand. Thus, those questions were asked only with regard to the brand that the respondents were mainly using. These questions were concerned with brand knowledge, brand commitment and brand overall attitude. The other questions that the respondents answered were about three other brands on the market. All dimensions, except purchase barriers, were measured on a ten-point scale.

SEM analysis was used to test the hypothesized MBE model as well as alternative models. The results, which supported the hypothesized model, indicated that knowledge has a strong positive effect on image, personality and attitude. Image has a positive effect on attitude, but that of personality was insignificant. Attitude, image and personality have a positive effect on commitment. Commitment affects recommendation strongly and positively. Both commitment and recommendation have a positive and significant effect on potential market share.

The limitations of the current research are that it was not measured over time and that only one product category has been tested. In addition to dealing with these limitations, future research may also add additional marketing performance outcome variables such as the ability to obtain premium prices and to exercise brand power in relation to channels of distribution.

The model presented in this paper provides the marketer with the ability to compare, from a competitive perspective, the relative average in the market place of customer mindset, customer performance and marketing performance. The analysis also reveals whether to invest in strengthening customer mindset or in capturing a greater market share. When the brand leader is far from its followers, an additional analysis may be required and it may be necessary to increase the sensitivity of the analysis by examining separately (without the leading brand) the relative differences between the follower brands. Moreover, the measurement questions should be adjusted to fit different product categories. For example, in testing the MBE in the service industry, “product performance,” which is a component of brand commitment, should be measured by the “quality of service.” But the way of using the model will not change. Another example for future research may be found in sport marketing, such as among football or basketball clubs. In such instances, performance – winning or losing – or even the quality of the players on the team may be considered. It is suggested here that the MBE’s measurement of fast-moving products vs slow moving ones. However, in such cases the model would probably show a significant difference in involvement with the brands of fast-moving products displaying much lower customers’ involvement then brands of slow-moving products.

The empirical model suggested in this study is a new and practical market-based brand equity that uses commitment as the main construct, building brand equity to represent the performance outcome of the customer mindset used in the models noted above. The current study also offers a new practical and useful formula for calculating and ranking MBE.

The intent of this research is determine the extent to which selfreported measures of fiscal condition are consistent with commonly identified measures of fiscal condition using secondary financial data. While the field of government finance has amassed a lengthy list of research on fiscal condition and fiscal stress assessment, there remains a gap in the research on the extent to which practitioners' perceptions of fiscal stress are consistent with such measures. Our results suggest that there is limited evidence of a relationship between self-reported and objective measures of fiscal condition

The purpose of this paper is to develop a model to assess and rank the financial risk of a municipal government (“municipality”). Financial risk is the likelihood that a municipality will experience financial distress.

Logistic regression is used with financial indicators to assess the level of financial risk. Then, the municipalities are ranked according to their financial risk. As predictor variables for the regression model, indicators are used that were developed by a Pennsylvania state agency to monitor the financial condition of municipalities.

Financial risk is positively associated with debt service, population, tax effort, and public service on roadways, while negatively correlated with intergovernmental revenues, operating position, user charges, capital outlays, fund balances, and tax revenue concentration. The financial risk model is able to correctly classify up to 99 percent of municipalities as either at risk or not at risk of financial distress.

The financial risk model was developed using data from one state in the USA. Further research is needed to test the model’s application to other states and countries.

Financial risk is on the rise since the Great Recession. This study may be used by municipal managers, citizens, creditors, and regulators to assess and rank the financial risk of a municipality.

This study provides a method of classifying municipalities as either at risk or not at risk of financial distress. Previous models of the financial condition of municipalities do not provide a method of assessing and ranking financial risk.

Identifying tools for predicting fiscally distressed local governments has received heightened attention following the Great Recession of 2007–2009. Despite the recent expansion of research, measuring fiscal distress is challenging because of the operational complexity associated with the term. Furthermore, many local governments are too small to produce a Comprehensive Annual Financial Report (CAFR), upon which many empirical studies of fiscal condition or fiscal distress are based. This study designs a parsimonious tool for identifying fiscally distressed entities based on existing literature. The authors examine Nebraska's 93 counties over a nine-year period (from 2010 to 2018). In order to ensure the validity of our tool, we replicate two well-known empirical approaches of assessing local fiscal condition and compare the results with ours. The authors find nearly all counties in Nebraska to be free from fiscal distress in the past decade. However, since most counties in Nebraska have small populations and are far from urban centers, they may still be vulnerable to future fiscal shocks and may need to closely monitor their fiscal condition.

The authors offer a parsimonious method for assessing the existence of fiscally distressed counties. They select predictors of fiscal distress based on two criteria. First, for the purpose of this study, the authors use financial information that is uniform, easily accessible and does not rely on CAFRs. In order to make their model parsimonious and replicable, the authors only consider factors that have the most decisive effects on local fiscal conditions. Second, the authors draw on indicators that have been consistently supported by previous studies (e.g., Kloha et al., 2005; Gorina et al., 2018). The authors test the validity of this approach using correlation analysis and regression modeling, similar to Wang et al. (2007).

The authors’ fiscal distress measure shows encouraging signs. Results show that all but Brown's model are highly correlated. The decile and standard deviation models have the strongest correlation (r = 0.955, p < 0.01). These two models are also significantly associated with Kloha et al.'s model. Their correlation coefficients are 0.812 and 0.830, respectively. Consistent with Wang et al. (2007), the authors find modest associations between our fiscal measures and socioeconomic measures.

Limitations include questions of generalizability – we are only studying Nebraska counties. The extent to which the findings are generalizable to counties in other states remains to be seen. We advise readers and policymakers to bear in mind that at this point, there is no perfect way to measure local fiscal condition or fiscal distress. Specifically, with our model, the foremost advantages of parsimony are data accessibility and replicability. However, unlike other existing tools that consider dozens of indicators, our tool bears the cost of not employing a more comprehensive perspective that may be required to capture a full picture of local fiscal condition.

The purpose of this research was to construct and present a parsimonious way of identifying local fiscal distress that is easily replicated and applied in practice. The challenges were operational – both in terms of definition and measurement. Fiscal distress is a nebulous concept that can vary based on the researcher's intent. Our chosen set of indicators have two characteristics: accessibility of financial information and consistency with past studies. Thus, we assess two of the four dimensions of solvency: budgetary solvency and long-run solvency. The authors suggest that this effort should not be used as a tool by state lawmakers to accuse and judge local governments. Instead, it should be used to assist local governments as Iowa and Colorado do. The findings could be the beginning of a conversation between the state and local governments to determine the best course(s) of action. As previously mentioned, there are many causes of fiscal distress and poor decision-making is not very common. Looking into the future, the authors expect more local governments to become fiscally distressed and the primary cause would be economic/demographic change. Since many local governments in Nebraska have very small populations and are far from the urban centers of Omaha and Lincoln, they might be vulnerable to future fiscal shocks. Thus, state lawmakers need to begin considering strategies to deal with local fiscal distress. The authors do have limitations in measurement. However, if used appropriately, this research can add value to the discussion of managing local government fiscal distress in Nebraska and other similar states.

While the analysis finds little fiscal distress currently in Nebraska, there is concern that with population migration to the urban areas and the “graying” of the state, local governments in rural areas (the vast majority in Nebraska) could face more serious issues in future years. A recent study showed that local fiscal condition is negatively associated with the distance from the municipality to the urban centers of Omaha and Lincoln (Maher et al., 2019). These spatial effects could be further exacerbated in a state that ranks near the bottom in financial support of local governments and policy makers are committed to “controlling” property taxes.

This study, while building on prior work, is unique in that it focuses on counties as opposed to municipalities, which are the most common units of analysis. The authors also offer a model for assessing fiscal distress in a state that currently does not have state-level systems to monitor local finances. Finally, rather than relying on audited annual financial reports which would disqualify many smaller local governments, the authors offer a parsimonious tool that is easily replicated and can be used by all local governments that submit uniform financial reports to their states.

This study aims to examine the relationship between job search self‐efficacy, employment goals, job search planning, job search behaviors and effort allocated to job search.

The authors expected that employment goals would mediate the effect of job search self‐efficacy on job search planning, job search behaviors and effort allocated to job search. In total, 100 participants completed measures of these concepts. The results are discussed with reference to previous studies and to methodological choices.

Regression analyses did not confirm the hypotheses. Contrary to expectations, employment goals did not mediate the path between self‐efficacy, job search planning, job search behaviors and effort allocated to job search. Instead, self‐efficacy directly influenced job search planning and job search behaviors.

Few studies have investigated the effect of self‐efficacy on goals in job search domain. This paper fills some of the gaps.

The purpose of this paper is to review the service quality dimensions established in various studies conducted across the world specifically applied to health care.

Studies conducted on quality of care selected from literature databases – Ebsco, Emerald Insight, ABI/Inform – was subjected to a comprehensive in-depth content analysis.

Service quality has been extensively studied with considerable efforts taken to develop survey instruments for measuring purposes. The number of dimensional structure varies across the studies. Self-administered questionnaire dominates in terms of mode of administration adopted in the studies, with respondents ranging from 18 to 85 years. Target sample size ranged from 84-2,000 respondents in self-administered questionnaires and for mail administration ranged from 300-2,600 respondents. Studies vary in terms of the scores used ranging from four to ten-point scale. A total of 27 of the studies have used EFA, 11 studies have used structural equation modelling and eight studies used gap scores. Cronbach ' s alpha is the most commonly used measure of scale reliability. There is variation in terms of measuring the content, criteria and construct validation among the studies.

The literature offers dimensions used in assessing patient perceived service quality. The review reveals diversity and a plethora of dimensions and methodology to develop the construct discussed.

The reported study describes and contrasts a large number of service-quality measurement constructs and highlights the usage of dimensions. The findings are valuable to academics in terms of dimensions and methodology used, approach for analysis; whereas findings are of value to practitioners in terms of the dimensions found in the research and to identify the gap in their setting.

The purpose of this paper is to investigate psychometric properties of the Self-Efficacy for Therapeutic Use of Self (SETUS) scales, a questionnaire based on the Intentional Relationship model, and to investigate the factor structure and internal consistency of the English version of three-part SETUS questionnaire in occupational therapy students.

The sample of this cross-sectional study included 155 students with age range 18–30 years, of which 95% were women. Principal Components Analysis (PCA) was performed on the questionnaire scales, including the Self-Efficacy for Therapeutic Mode Use (SETMU), Self-Efficacy for Recognizing Interpersonal Characteristics (SERIC) and Self-Efficacy for Managing Interpersonal Events (SEMIE). The internal consistencies were calculated. Pearson correlation analysis was used to evaluate the strength of correlation among the scales.

The PCA confirmed that the items of each of the three proposed scales loaded strongly on one factor (self-efficacy for three factors of therapeutic mode use, recognizing interpersonal characteristics and managing interpersonal events). The Cronbach’s alpha for the SETMU, SERIC and SEMIE was 0.85, 0.95 and 0.96, respectively. The three scales significantly inter-correlated strongly (r ranging 0.74–0.83, all p < 0.001).

The SETUS questionnaire comprises three valid and reliable scales. It can be used by occupational therapy supervisors as a means to reflect on students’ self-efficacy in components of therapeutic use of self.

This paper analyzes the connection between black political protest and mobilization, and the rise and fall of a black urban regime. The case of Oakland is instructive because by the mid-1960s the ideology of “black power” was important in mobilizing two significant elements of the historically disparaged black community: (1) supporters of the Black Panthers and, (2) neighborhood organizations concentrated in West Oakland. Additionally, Oakland like the city of Atlanta also developed a substantial black middle class that was able to mobilize along the lines of its own “racialized” class interests. Collectively, these factors were important elements in molding class-stratified “black power” and coalitional activism into the institutional politics of a black urban regime in Oakland. Ultimately, reversal factors would undermine the black urban regime in Oakland. These included changes in the race and class composition of the local population: black out-migration, the “new immigration,” increasing (predominantly white) gentrification, and the continued lack of opportunity for poor and working-class blacks, who served as the unrequited base of the black urban regime. These factors would change the fortunes of black political life in Oakland during the turbulent neoliberal era.