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Book part
Publication date: 1 August 2012

Andreas Schwab and William H. Starbuck

Purpose – This chapter reports on a rapidly growing trend in the analysis of data about emerging market (EM) economies – the use of baseline models as comparisons for…

Abstract

Purpose – This chapter reports on a rapidly growing trend in the analysis of data about emerging market (EM) economies – the use of baseline models as comparisons for explanatory models. Baseline models estimate expected values for the dependent variable in the absence of a hypothesized causal effect but set higher standards than do traditional null hypotheses tests that expect no effect.

Design/methodology/approach – Although the use of baseline models research originated in the 1960s, it has not been widely discussed, or even acknowledged, in the EM literature. We surveyed published EM studies to determine trends in the use of baseline models.

Findings – We categorize and describe the different types of baseline models that scholars have used in EM studies, and draw inferences about the differences between more effective and less effective uses of baseline models.

Value – We believe that comparisons with baseline models offer distinct methodological advantages for the iterative development of better explanatory models and a deeper understanding of empirical phenomena.

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West Meets East: Toward Methodological Exchange
Type: Book
ISBN: 978-1-78190-026-0

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Book part
Publication date: 30 May 2013

Andreas Schwab and William H. Starbuck

This chapter reports on a rapidly growing trend in data analysis – analytic comparisons between baseline models and explanatory models. Baseline models estimate values for…

Abstract

This chapter reports on a rapidly growing trend in data analysis – analytic comparisons between baseline models and explanatory models. Baseline models estimate values for the dependent variable in the absence of hypothesized causal effects. Thus, the baseline models discussed in this chapter differ from the baseline models commonly used in sequential regression analyses.Baseline modelling entails iteration: (1) Researchers develop baseline models to capture key patterns in the empirical data that are independent of the hypothesized effects. (2) They compare these patterns with the patterns implied by their explanatory models. (3) They use the derived insights to improve their explanatory models. (4) They iterate by comparing their improved explanatory models with modified baseline models.The chapter draws on methodological literature in economics, applied psychology, and the philosophy of science to point out fundamental features of baseline modelling. Examples come from research in international business and management, emerging market economies and developing countries.Baseline modelling offers substantial advantages for theory development. Although analytic comparisons with baseline models originated in some research fields as early as the 1960s, they have not been widely discussed or applied in international management. Baseline modelling takes a more inductive and iterative approach to modelling and theory development. Because baseline modelling holds substantial potential, international-management scholars should explore its opportunities for advancing scientific progress.

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Philosophy of Science and Meta-Knowledge in International Business and Management
Type: Book
ISBN: 978-1-78190-713-9

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Book part
Publication date: 14 July 2004

Kalman Rupp and Paul S Davies

Using data from the Survey of Income and Program Participation (SIPP) matched to administrative records, we examine mortality risk and participation in the Disability…

Abstract

Using data from the Survey of Income and Program Participation (SIPP) matched to administrative records, we examine mortality risk and participation in the Disability Insurance (DI) and Supplemental Security Income (SSI) disability programs from a long-term perspective. Over a period of 14 years, we analyze the effect of self-reported health and disability on the probability of death and disability program entry among individuals aged 18–48 in 1984. We also assess DI and SSI programs from a life-cycle perspective. Self-reported poor health and severe disability at baseline are strongly correlated with death over the 14-year follow-up period. These variables also are strong predictors of disability program participation over the follow-up period among non-participants at baseline or before, with increasing marginal probabilities in the out-years. Our cross-sectional models are consistent with recent studies that find that the work-prevented measure is useful in modeling DI entry. However, once self-reported health and functional limitations are accounted for, the longitudinal entry models provide conflicting DI results for the work-prevented measure, suggesting that, contrary to claims based on cross-sectional or short-time horizon application models, the work-prevented measure is an unreliable indicator of severity. The risk of SSI and DI participation is significantly greater for individuals who die, suggesting that future mortality captures the effect of case severity and deterioration of health during the follow-up period. From a life-cycle perspective, a substantially greater proportion of individuals participate in SSI or DI at some point in their lives compared to typical cross-sectional estimates of participation, especially among minorities, people with less than a high school education, and those with early onset of poor health and/or disabilities. Cross-sectional estimates for the Social Security area population indicate SSI and DI participation rates of no more than 5% combined in 2000. In contrast, for individuals aged 43–48 in 1984, we observe a cumulative lifetime SSI and/or DI participation rate of 14%. The corresponding figure is 32% for individuals in that age group who did not graduate from high school, suggesting the need for human capital investments and/or improved work incentives.

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Accounting for Worker Well-Being
Type: Book
ISBN: 978-1-84950-273-3

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Article
Publication date: 15 May 2017

Andrea M. Sevene, John E. Edlund and Caroline J. Easton

The purpose of this paper is to address a possible interaction of cognitive distortions associated with substance dependency and intimate partner violence (IPV), and the…

Abstract

Purpose

The purpose of this paper is to address a possible interaction of cognitive distortions associated with substance dependency and intimate partner violence (IPV), and the effects on subsequent behavior. The primary focus was to investigate the relationship between offender perception (i.e. perception of family problems (FP) and perception of need for treatment for family problems (FPTx)) and treatment outcome (i.e. substance use and violence), among a unique sample of substance dependent male offenders of IPV. An additional investigation included the change in perception from baseline to the end of treatment.

Design/methodology/approach

In total, 63 participants were randomly assigned to one of two treatment conditions and assessed across 12 weeks of treatment.

Findings

Participants in the (FP+) (i.e. those who perceived family problems at baseline) and (FPTx+) (i.e. those who perceived a need for treatment for family problems at baseline) conditions reported a significantly greater change in the number of days of violence from baseline to the end of treatment, compared to participants in the (FP−) (i.e. those who did not perceive family problems at baseline) and (FPTx−) (i.e. participants who perceived no need for treatment at baseline) conditions. (FP+) and (FPTx+) participants had significant decreases in any violent behavior from pre- to post-treatment.

Originality/value

The results of this study highlight the importance of techniques aimed at improving clients’ ability to recognize and admit to problem behaviors, a critical component of cognitive-behavioral therapy, in an effort to increase their motivation for treatment, thus leading to greater treatment success.

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Advances in Dual Diagnosis, vol. 10 no. 2
Type: Research Article
ISSN: 1757-0972

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The Peace Dividend
Type: Book
ISBN: 978-0-44482-482-0

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Article
Publication date: 23 November 2010

Pierce H. Jones, Nicholas W. Taylor, M. Jennison Kipp and Harold S. Knowles

This paper seeks to describe a protocol to estimate annual community energy consumption baselines for single‐family detached homes in the Gainesville Regional Utility…

Abstract

Purpose

This paper seeks to describe a protocol to estimate annual community energy consumption baselines for single‐family detached homes in the Gainesville Regional Utility service area of Alachua County, Florida, USA. Further, it details methods using these baselines to make direct comparisons of individual households' energy consumption and evaluate the energy impacts of three prescriptive demand side management (DSM) programs.

Design/methodology/approach

To improve estimates of energy savings, the paper proposes using a “micro” scale multivariate regression methodology based on a census of utility and property appraiser household data.

Findings

Results suggest that traditional analysis approaches are likely to overestimate savings significantly and that the annual community baseline technique provides more consistent estimates of energy savings than most commonly used methods.

Practical implications

This type of analysis could provide a tool that utilities can use to more accurately and cost effectively measure DSM savings. This could result in reduced energy demand related to streamlined program setup and management.

Originality/value

The proposed methodology is unique in that it defines a new household‐level energy consumption baseline measure that we think is a more appropriate performance measure, uses a census of publicly available data for the population of interest, merging metered utility data with property appraiser data, and works upward to construct a simple model for evaluating household‐level energy consumption. The critical element that distinguishes our proposed energy performance measures is that they are calculated and interpreted using annual, population‐level, comparison‐group baselines that effectively normalize for community energy consumption patterns in any given year.

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International Journal of Energy Sector Management, vol. 4 no. 4
Type: Research Article
ISSN: 1750-6220

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Article
Publication date: 11 March 2014

Bart Lariviere, Timothy L. Keiningham, Bruce Cooil, Lerzan Aksoy and Edward C. Malthouse

This study aims to provide the first longitudinal examination of the relationship between affective, calculative, normative commitment and customer loyalty by using…

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Abstract

Purpose

This study aims to provide the first longitudinal examination of the relationship between affective, calculative, normative commitment and customer loyalty by using longitudinal panel survey data.

Design/methodology/approach

Repeated measures for 269 customers of a large financial services provider are employed. Two types of segmentation methods are compared: predefined classes and latent class models and predictive power of different models contrasted.

Findings

The results reveal that the impact that different dimensions of commitment have on share development varies across segments. A two-segment latent class model and a managerially relevant predefined two-segment customer model are identified. In addition, the results demonstrate the benefits of using panel survey data in models that are designed to study how loyalty develops over time.

Practical implications

This study illustrates the benefits of including both baseline level information and changes in the dimensions of commitment in models that try to understand how loyalty unfolds over time. It also demonstrates how managers can be misled by assuming that everyone will react to commitment improvement efforts similarly. This study also shows how different segmentation schemes can be employed and reveals that the most sophisticated ones are not necessarily the best.

Originality/value

This research provides the first examination of models for change in customer loyalty by employing survey panel data on the three-component model of customer commitment (affective, calculative, and normative) and considers alternative segmentation methods.

Details

Journal of Service Management, vol. 25 no. 1
Type: Research Article
ISSN: 1757-5818

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Article
Publication date: 7 June 2021

Elizabeth Louisa Roos and Philip David Adams

This paper aims to provide a quantitative assessment of the broad economic effects of tax policy reform in the Kingdom of Saudi Arabia (KSA).

Abstract

Purpose

This paper aims to provide a quantitative assessment of the broad economic effects of tax policy reform in the Kingdom of Saudi Arabia (KSA).

Design/methodology/approach

Using a dynamic computable general equilibrium (CGE) model of the KSA, three simulations are run. The first simulation is the baseline simulation, which generates growth paths of the Saudi economy in the absence of tax reform. In developing the baseline simulation, this study incorporates forecasts from the International Monetary Fund. The remaining simulations are policy simulations. A policy simulation deviates from the baseline simulation in response to a policy change. In the first policy simulation, this study introduces a value-added tax (VAT) that generates SAR 35bn. This study assumes budget neutrality with the additional tax revenue transferred to households via a lump sum payment. In the second policy simulation, this study introduces a corporate income tax that generates SAR 35bn. This study then calculates and compares the distortion these taxes introduce into the economy.

Findings

This study finds that although the introduction of new taxes increases government tax revenue, markets are distorted lowering efficiency and production. An introduction of VAT increases the cost of consumption relative to the cost of production. As a consequence, the real cost of labour increases lowering employment in the short run. Employment moves to the baseline, as wages adjust capital and real gross domestic product (GDP) is below base throughout the simulation period. The second simulation is an increase in the corporate tax rate with lowers the post-tax rates of return investors receive. This simulation shows that the negative impact on investment, capital and GDP is larger with the introduction of a corporate tax than with the VAT.

Research limitations/implications

Literature focusing on tax policy reform in the Gulf Cooperation Council and, specifically, Saudi Arabia is limited. This paper contributes to the literature by focusing on the following: understanding the impact and mechanisms through which changes in taxation impact the economy more generally; understanding the potential harm caused to allocative efficiency and production due to taxes; and ways in which fiscal reform might complement other reforms such as efforts to diversify the economy, labour market and energy price reforms. This improves the information base available to policymakers charged with designing an optimal tax system that meets all future requirements of a country such as the KSA.

Originality/value

The authors developed and applied a CGE model for the KSA to analyse the impact of VAT and corporate tax on the Saudi economy. To the best of the authors’ knowledge, there are no recent CGE models for Saudi Arabia that have been used for tax policy or quantifying the potential harm to the economy when new taxes are introduced.

Details

International Journal of Islamic and Middle Eastern Finance and Management, vol. 14 no. 4
Type: Research Article
ISSN: 1753-8394

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Modern Energy Market Manipulation
Type: Book
ISBN: 978-1-78743-386-1

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Article
Publication date: 8 February 2021

Keng Hoon Gan and Noeurn Krol

Customer reviews are one important source that contains valuable information for quality evaluation of products or services. Review sentences contain sentiment words that…

Abstract

Purpose

Customer reviews are one important source that contains valuable information for quality evaluation of products or services. Review sentences contain sentiment words that show whether a user’s opinion is positive or negative. When review sentence has mix opinions, having sentiment words of both polarities, it is difficult to conclude whether it is positive or negative opinion. The purpose of this study is to improve the detection of polarity in such situation.

Design methodology approach

In this research, methods such as part-of-speech tagging, polarity analysis and rules selection are used to identify the polarity. A set of rules called contrast and conditional polarity rules (CCPR) has been created to improve the polarity detection in cases when there is mixture of sentiment words used in contrast and conditional type of review sentences. The experiment is conducted with data sets from three domains, i.e. restaurant, electronic and Tripadvisor.

Findings

The experimental result confirms that CCPR rules have higher baseline of the polarity aggression. In restaurant domain, CCPR rules (62.07%) have increased 13.79% compared with the Pol_Agg_MPQA baseline (48.28%) and 13.79% compared with Pol_Agg_Senti baseline (48.28%). In electronic domain, CCPR rule (79.17%) is higher by 12.50% compared with the Pol_Agg_MPQA baseline (66.67%) and 16.67% compared with Pol_Agg_Senti baseline (62.50%). Another one, CCPR rule (70.83%) is higher by 8.33% compared with the Pol_Agg_MPQA baseline (62.50%) and 12.50% compared with Pol_Agg_Senti baseline (58.33%). In conclusion, result of experiment shows promising outcome with improvement in detecting the positivity and negativity of indirect sentence, especially for the case of sentence with indirect polarity.

Originality value

To address the problem of mix opinions in terms of polarities, this paper presents a rule-based approach to improve the result of identifying positivity and negativity in sentence with indirect polarities.

Details

International Journal of Web Information Systems, vol. 17 no. 2
Type: Research Article
ISSN: 1744-0084

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