scholarly journals Motives for Mergers and Acquisitions in the Nepalese Perspective

2018 ◽  
Vol 13 ◽  
pp. 9 ◽  
Author(s):  
Hari Prasad Pathak
Keyword(s):  
Factor Analysis ◽  
Mergers And Acquisitions ◽  
Economies Of Scale ◽  
Ordinary Least Squares ◽  
Survey Method ◽  
Least Squares Regression ◽  
Economic Literature ◽  
Regulatory Requirement ◽  
Second Stage ◽  
Synergistic Gains

<p>This paper attempts to identify the motives of mergers and acquisitions in the Nepalese financial sector.Questionnaire survey method is used to obtain the views of randomly selected 122 bankers of 21 post-merged financial institutions.A two-stage multivariate procedure is used to identify the important factors that drive the merger of financial institutions.In the first stage, an exploratory factor analysis is performed using ten statements that were put in the Likert scale in the questionnaire. In the second stage, important motives of mergers are determined by conducting an ordinary least squares regression using the factors extracted from factor analysis. It checks the internal consistency and reliability of the data using the Cronbach’s Alpha. The paper concludes hat the three most important motives for mergers of Nepalese financial institutions are: (i)meeting the regulatory requirement of paid up capital, (ii) realization of economies of scale and scope, and (iii) generation of efficiencies due to synergistic gains.</p><p> <strong><em>Economic Literature</em></strong><em>, </em>Vol. XIII August 2016, page: 9-18</p><p> </p>

Exploring consumers' response to text-based chatbots in e-commerce: the moderating role of task complexity and chatbot disclosure

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Xusen Cheng ◽  
Ying Bao ◽  
Alex Zarifis ◽  
Wankun Gong ◽  
Jian Mou
Keyword(s):  
Task Complexity ◽  
Deep Understanding ◽  
Ordinary Least Squares ◽  
Survey Method ◽  
Least Squares Regression ◽  
Moderating Effects ◽  
Content Type ◽  
Identity Disclosure ◽  
The Relationship

PurposeArtificial intelligence (AI)-based chatbots have brought unprecedented business potential. This study aims to explore consumers' trust and response to a text-based chatbot in e-commerce, involving the moderating effects of task complexity and chatbot identity disclosure.Design/methodology/approachA survey method with 299 useable responses was conducted in this research. This study adopted the ordinary least squares regression to test the hypotheses.FindingsFirst, the consumers' perception of both the empathy and friendliness of the chatbot positively impacts their trust in it. Second, task complexity negatively moderates the relationship between friendliness and consumers' trust. Third, disclosure of the text-based chatbot negatively moderates the relationship between empathy and consumers' trust, while it positively moderates the relationship between friendliness and consumers' trust. Fourth, consumers' trust in the chatbot increases their reliance on the chatbot and decreases their resistance to the chatbot in future interactions.Research limitations/implicationsAdopting the stimulus–organism–response (SOR) framework, this study provides important insights on consumers' perception and response to the text-based chatbot. The findings of this research also make suggestions that can increase consumers' positive responses to text-based chatbots.Originality/valueExtant studies have investigated the effects of automated bots' attributes on consumers' perceptions. However, the boundary conditions of these effects are largely ignored. This research is one of the first attempts to provide a deep understanding of consumers' responses to a chatbot.

scholarly journals Impact of Financial and Non-financial Benefit on Employees’ Job Satisfaction

2020 ◽  
Vol 3 (1) ◽  
pp. 85-94
Author(s):  
Prem Bahadur Budhathoki
Keyword(s):  
Job Satisfaction ◽  
Career Development ◽  
Pearson Correlation ◽  
Ordinary Least Squares ◽  
Primary Data ◽  
Survey Method ◽  
Least Squares Regression ◽  
Financial Benefit ◽  
Development Opportunity ◽  
The Impact

This study examines the impact of financial benefit, training, reward, and career development opportunity on employees’ job satisfaction. This study is based on Likert scale data. There are forty questions included in the questionnaires excluding demographic variables. Each attribute contains eight questions. The primary data are obtained through the survey method. These collected data are analyzed by using descriptive statistics, Pearson correlation coefficient, and ordinary least squares regression model. The Statistics Package for Social Sciences (SPSS) is used for the analysis of data. The results indicate that the independent variables (financial benefit, training, reward, and career development opportunity) positively impact on job satisfaction.

scholarly journals Model Correlates Many Factors to Undergraduates’ Perceived Importance of Library and Research Activities, but Low Explanation Power Suggests More Research Needed

2014 ◽  
Vol 9 (2) ◽  
pp. 16
Author(s):  
Diana K. Wakimoto
Keyword(s):  
Factor Analysis ◽  
Student Perceptions ◽  
Undergraduate Students ◽  
Academic Engagement ◽  
The United States ◽  
Ordinary Least Squares ◽  
Least Squares Regression ◽  
Academic Variables ◽  
Research Activities ◽  
World Class

A Review of: Soria, K. M. (2013). Factors predicting the importance of libraries and research activities for undergraduates. Journal of Academic Librarianship, 39(6), 464-470. Objective – The purpose is to analyze characteristics and perceptions of undergraduate students to determine factors that predict the importance of library and research activities for the students. Design – Student Experience in the Research University (SERU) survey questionnaire. Setting – Nine large, public, research universities in the United States of America. Subjects – 16,778 undergraduates who completed the form of the survey that included the academic engagement module questions. Methods – The researcher used descriptive and inferential statistics to analyze student responses. Descriptive statistics included coding demographic, collegiate, and academic variables, as well as student perceptions of the importance of library and research activities. These were used in the inferential statistical analyses. Ordinary least squares regression and factor analysis were used to determine variables and factors that correlated to students’ perceptions of the importance of libraries and research activities. Main Results – The response rate for the overall SERU survey was 38.1%. The results showed that the majority of students considered having access to a “world-class library collection,” learning research methods, and attending a university with “world-class researchers” to be important. The regression model explained 22.7% of variance in the importance students placed on libraries and research activities; factors important to the model covered demographics, collegiate, and academic variables. Four variables created in factor analysis (academic engagement, library skills, satisfaction with libraries and research, and faculty interactions) were significantly correlated with the importance students placed on libraries and research activities. The most important predictors in the model were: student satisfaction, interest in a research or science profession, interest in medical or health-related profession, academic engagement, and academic level. Conclusion – Based on the results of this study, librarians should be able to tailor their marketing to specific student groups to increase the perception of importance of libraries by undergraduates. For example, more success may be had marketing to students who are Hispanic, Asian, international, interested in law, psychology or research professions as the study found these students place more importance on libraries and research activities than other groups. These students may be targeted for being peer advocates for the libraries. Further research is suggested to more fully understand factors that influence the value undergraduate students place on libraries and find ways to increase the value of libraries and research activities for those demographic groups who currently rate the importance lower.

scholarly journals The Impact of Merger and Acquisition on Customer Satisfaction in Post- Merger Phase in Banking Sector of Nepal

2018 ◽  
Vol 11 (1) ◽  
pp. 57-69
Author(s):  
Krishna Prasad Sharma
Keyword(s):  
Customer Satisfaction ◽  
Service Quality ◽  
Mergers And Acquisitions ◽  
Customer Service ◽  
Financial Institutions ◽  
Economies Of Scale ◽  
Weighted Average ◽  
Survey Method ◽  
Satisfaction Level ◽  
The Impact

Mergers and acquisitions among financial institutions have been increased due to the introduction of merger by-law in May 2011 and capital enhancement through monetary policy of Nepal Rastra Bank in 2015. Bank and financial institutions need to be fully approachable and reactive that banking merger has not hampered customer service. Since the entire business depends on the customer’s positive feedback and satisfaction, good customer service is essential in this kind of business. It is always being argued that the impact of mergers and acquisitions on the customer is difficult to measure due to the direct influence of external factors like global competition or technological advancement. Bearing this consideration, the paper evaluates the impact of bank mergers and acquisitions on customers by using survey method. Customer satisfaction and service quality after mergers have been measured by summative scale calculated by a simple arithmetic mean and by using the weighted average method. Similarly, five point Likert-type scales have been used for measuring the satisfaction level of customer. Customers were asked to rank the various factors affecting satisfaction level on the five point scale which was further analyzed using SPSS and MS Excel. Results suggest that the merger program was successful from customers’ point of view in Nepal because it has benefited them through economies of scale, expansion of working area and advancement in technology. Another perspective regarding the service quality of banks in post-merger found that customers are enjoying competitive interest rate due to the enhanced capital base.

scholarly journals Least Likely Observations in Regression Models for Categorical Outcomes

2002 ◽  
Vol 2 (3) ◽  
pp. 296-300 ◽  
Author(s):  
Jeremy Freese
Keyword(s):  
Logistic Regression ◽  
Regression Models ◽  
Binary Logistic Regression ◽  
Positive Outcome ◽  
Ordinary Least Squares ◽  
Parameter Estimates ◽  
Least Squares Regression ◽  
Binary Logistic Regression Model ◽  
Ordered Logistic Regression ◽  
Negative Outcome

This article presents a method and program for identifying poorly fitting observations for maximum-likelihood regression models for categorical dependent variables. After estimating a model, the program leastlikely will list the observations that have the lowest predicted probabilities of observing the value of the outcome category that was actually observed. For example, when run after estimating a binary logistic regression model, leastlikely will list the observations with a positive outcome that had the lowest predicted probabilities of a positive outcome and the observations with a negative outcome that had the lowest predicted probabilities of a negative outcome. These can be considered the observations in which the outcome is most surprising given the values of the independent variables and the parameter estimates and, like observations with large residuals in ordinary least squares regression, may warrant individual inspection. Use of the program is illustrated with examples using binary and ordered logistic regression.

Home Health Agencies: Empirical Evidence on the Patient-Driven Groupings Model’s Expected Effects on Agency Reimbursements

2021 ◽  
pp. 108482232199038
Author(s):  
Elizabeth Plummer ◽  
William F. Wempe
Keyword(s):  
Ordinary Least Squares ◽  
Process Quality ◽  
Home Health ◽  
Least Squares Regression ◽  
Residual Variation ◽  
Health Agencies ◽  
Dual Eligible ◽  
Home Health Agencies ◽  
Seriously Ill Patients ◽  
Seriously Ill

Beginning January 1, 2020, Medicare’s Patient-Driven Groupings Model (PDGM) eliminated therapy as a direct determinant of Home Health Agencies’ (HHAs’) reimbursements. Instead, PDGM advances Medicare’s shift toward value-based payment models by directly linking HHAs’ reimbursements to patients’ medical conditions. We use 3 publicly-available datasets and ordered logistic regression to examine the associations between HHAs’ pre-PDGM provision of therapy and their other agency, patient, and quality characteristics. Our study therefore provides evidence on PDGM’s likely effects on HHA reimbursements assuming current patient populations and service levels do not change. We find that PDGM will likely increase payments to rural and facility-based HHAs, as well as HHAs serving greater proportions of non-white, dual-eligible, and seriously ill patients. Payments will also increase for HHAs scoring higher on quality surveys, but decrease for HHAs with higher outcome and process quality scores. We also use ordinary least squares regression to examine residual variation in HHAs’ expected reimbursement changes under PDGM, after accounting for any expected changes related to their pre-PDGM levels of therapy provision. We find that larger and rural HHAs will likely experience residual payment increases under PDGM, as will HHAs with greater numbers of seriously ill, younger, and non-white patients. HHAs with higher process quality, but lower outcome quality, will similarly benefit from PDGM. Understanding how PDGM affects HHAs is crucial as policymakers seek ways to increase equitable access to safe and affordable non-facility-provided healthcare that provides appropriate levels of therapy, nursing, and other care.

scholarly journals Relationships between Final Purchasers and Offerors in the Context of Their Perception by Final Purchasers

Energies ◽  
2021 ◽  
Vol 14 (11) ◽  
pp. 3271
Author(s):  
Agnieszka Izabela Baruk
Keyword(s):  
Factor Analysis ◽  
Statistical Analysis ◽  
World Literature ◽  
Empirical Studies ◽  
Primary Data ◽  
Survey Method ◽  
Chi Square ◽  
Marketing Process ◽  
Research Gap

The aim of this article was to identify the role of good mutual relationships with offerors for final purchasers, as well as define the meaning of the perception of offerors in the scope of listening to purchasers’ opinions and profiting from purchasers’ readiness to cooperate for the specificities of the prosumeric activity. A deep analysis of the world literature was used to prepare the theoretical part of this paper. The results of this analysis confirm the existing cognitive gap and research gap regarding mentioned aspects, including energy market. Empirical studies were conducted to reduce identified gaps. The survey method was used to collect primary data. The collected data were subjected to quantitative analysis, during which statistical analysis methods and tests were applied (Pearson chi-square independence test, V-Cramer factor analysis, Kruskal–Wallis test (KW), and exploratory factor analysis). The results of the statistical analysis and testing allowed the three research hypotheses formulated to be checked. Between the significance of good relationships with offerors and their perception, a statistically significant dependence was identified for all groups of offerors. The perception of offerors was a feature differentiating respondents’ opinions about the significance of good relationships with offerors for the two following groups: producers and traders. Additionally, the perception of offerors was a feature differentiating forms of prosumeric activity of respondents only for three interpurchase behaviors. The results obtained have a visible cognitive and applicability value. They contribute to the theory of marketing, as well as possibly facilitating the formation of good mutual relationships between offerors (including offerors of energy) and final purchasers as key partners cooperating with offerors in the marketing process. The approach presented in this paper has not been studied and analyzed so far, either in theoretical or in practical terms. This fact confirms its originality and value.

scholarly journals Predicting presenteeism using measures of health status

2021 ◽  
Author(s):  
Cheryl Jones ◽  
Katherine Payne ◽  
Alexander Thompson ◽  
Suzanne M. M. Verstappen
Keyword(s):  
Health Status ◽  
Online Survey ◽  
Activity Index ◽  
Work Productivity ◽  
Rank Correlation ◽  
Ordinary Least Squares ◽  
Statistical Correlation ◽  
Least Squares Regression ◽  
Mapping Algorithm ◽  
Spearman’S Rank Correlation

Abstract Objectives To identify whether it is feasible to develop a mapping algorithm to predict presenteeism using multiattribute measures of health status. Methods Data were collected using a bespoke online survey in a purposive sample (n = 472) of working individuals with a self-reported diagnosis of Rheumatoid arthritis (RA). Survey respondents were recruited using an online panel company (ResearchNow). This study used data captured using two multiattribute measures of health status (EQ5D-5 level; SF6D) and a measure of presenteeism (WPAI, Work Productivity Activity Index). Statistical correlation between the WPAI and the two measures of health status (EQ5D-5 level; SF6D) was assessed using Spearman’s rank correlation. Five regression models were estimated to quantify the relationship between WPAI and predict presenteeism using health status. The models were specified based in index and domain scores and included covariates (age; gender). Estimated and observed presenteeism were compared using tenfold cross-validation and evaluated using Root mean square error (RMSE). Results A strong and negative correlation was found between WPAI and: EQ5D-5 level and WPAI (r = − 0.64); SF6D (r =− 0.60). Two models, using ordinary least squares regression were identified as the best performing models specifying health status using: SF6D domains with age interacted with gender (RMSE = 1.7858); EQ5D-5 Level domains and age interacted with gender (RMSE = 1.7859). Conclusions This study provides indicative evidence that two existing measures of health status (SF6D and EQ5D-5L) have a quantifiable relationship with a measure of presenteeism (WPAI) for an exemplar application of working individuals with RA. A future study should assess the external validity of the proposed mapping algorithms.

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