Consumers\u27 Perceptions of Voluntary and Involuntary Deconsumption: An Exploratory Sequential Scale Development Study

This exploratory sequential mixed methods study of scale development was conducted among baby boomers in the United States to render conceptual clarity to the concepts of voluntary and involuntary deconsumption, to explore deconsumption behavior under the tenets of the attribution theory of motivation, and to examine the components, structures, uses, and measurement properties of scales of voluntary and involuntary deconsumption. It was also an attempt to reiterate the importance of the baby boomer segment(s) for marketing practitioners based on growth, economic viability, and the power of influence, and to establish a deep understanding of the deconsumption processes, which could enable marketers to devise strategies to pre-emptively avoid, pro-actively influence, and/or reactively mitigate deconsumption outcomes. The critical incident in a relationship context (CIRC) technique was used in conjunction with grounded theory approach in the qualitative phase (study 1); and survey research, principal components analysis, and Rasch analysis were used in the quantitative phase (study 2). Behavioral process theories of the experience of voluntary and involuntary deconsumption were posited; and motivations and consequences of both types of deconsumption were discussed. The differences in the experience of deconsumption based on variables such as deconsumption type (voluntary and involuntary), gender (male and female), and baby boomer type (trailing- and leading-edge) were explained as well. Subscales of voluntary deconsumption included four components, i.e., elevated state of purpose, social agency and activism, non-materialism, and acceptance of life circumstances. Subscales of involuntary deconsumption included three components, i.e., victim mentality, materialism, and non-acceptance of life circumstances. Finally, the unidimensionality, appropriate scale use, invariance, and levels of validity and reliability of all the subscales of voluntary and involuntary deconsumption were tested, and reported as acceptable and appropriate. In conclusion, the implications of the results for theory, research methodology, and practice were discussed, and recommendations for future research inquiry were made

Promoting work Engagement in the Accounting Profession: a Machine Learning Approach

In this paper, a non-linear multi-dimensional (machine learning-based) index for accountants that relates work engagement scores (according to accountants’ perceptions) with the seven Job Quality Indices (JQI) (proposed by Eurofound) has been proposed. The goal of the research is two-fold, namely, (i) to quantify the extent to which the JQI variables explain the work engagement scores, and (ii) to determine which JQI variables most afect the work engagement scores. The best performing regression model achieved a competitive root mean square percentage, highlighting that the selected variables primarily determine the work engagement values. Other important fndings include (i) that the work engagement index is mainly infuenced by the social environment index and (ii) that the skills and discretion and prospects indices are also crucial in the promotion of the work engagement of accountants. The instrument implemented could be employed by human resources practitioners to propose efcient human resources strategies that improve both individual wellbeing and company performance in the accounting sector

ADAPTS: An Intelligent Sustainable Conceptual Framework for Engineering Projects

This paper presents a conceptual framework for the optimization of environmental sustainability in engineering projects, both for products and industrial facilities or processes. The main objective of this work is to propose a conceptual framework to help researchers to approach optimization under the criteria of sustainability of engineering projects, making use of current Machine Learning techniques. For the development of this conceptual framework, a bibliographic search has been carried out on the Web of Science. From the selected documents and through a hermeneutic procedure the texts have been analyzed and the conceptual framework has been carried out. A graphic representation pyramid shape is shown to clearly define the variables of the proposed conceptual framework and their relationships. The conceptual framework consists of 5 dimensions; its acronym is ADAPTS. In the base are: (1) the Application to which it is intended, (2) the available DAta, (3) the APproach under which it is operated, and (4) the machine learning Tool used. At the top of the pyramid, (5) the necessary Sensing. A study case is proposed to show its applicability. This work is part of a broader line of research, in terms of optimization under sustainability criteria.Telefónica Chair “Intelligence in Networks” of the University of Seville (Spain

Sustainable consumption: towards action and impact. : International scientific conference November 6th-8th 2011, Hamburg - European Green Capital 2011, Germany: abstract volume

This volume contains the abstracts of all oral and poster presentations of the international scientific conference „Sustainable Consumption – Towards Action and Impact“ held in Hamburg (Germany) on November 6th-8th 2011. This unique conference aims to promote a comprehensive academic discourse on issues concerning sustainable consumption and brings together scholars from a wide range of academic disciplines. In modern societies, private consumption is a multifaceted and ambivalent phenomenon: it is a ubiquitous social practice and an economic driving force, yet at the same time, its consequences are in conflict with important social and environmental sustainability goals. Finding paths towards “sustainable consumption” has therefore become a major political issue. In order to properly understand the challenge of “sustainable consumption”, identify unsustainable patterns of consumption and bring forward the necessary innovations, a collaborative effort of researchers from different disciplines is needed

The economics of child well-being

This paper presents an integrated economic approach that organizes and interprets the evidence on child development. It also discusses the indicators of child well-being that are used in international comparisons. Recent evidence on child development is summarized, and policies to promote child well-being are discussed. The chapter concludes with some open questions and suggestions for future research

Understanding ethical consumption decisions: The role of values, attitudes and expectations in the apparel purchasing context

This study provides understanding of factors that affect U.S. consumers\u27 intentions to patronize apparel retail brands that are engaged in corporate social responsibility (CSR). The present study developed a research model based on a dual theoretical framework - theory of reasoned action (TRA) and expectations confirmation theory (ECT). Causal relationships between personal values (universalism and benevolence), moral norms, knowledge of environmental and social issues within the apparel industry, expectations, attitudes and intentions to patronize apparel retail brands engaged in CSR were examined. Data were collected via a web-based survey from a national sample of U.S. consumers who were recruited using the services of a market research company specializing in consumer panel studies - Survey Sampling International (SSI, n.d.). A total of 405 completed surveys were used for the statistical analysis. Preliminary analysis of research data consisted of descriptive analysis, principal components analysis, internal reliability assessment of research variables, and correlation analysis. Confirmatory factor analysis for each construct and measurement model testing was performed. Latent variable structural model testing was conducted for three models - fully recursive, hypothesized model and alternate model using Mplus statistical software (Muthén & Muthén, 2000). Findings of the present study revealed that consumers\u27 knowledge of environmental issues in the apparel industry, moral norms, expectations of ethical behavior, attitudes towards patronizing apparel retail brands engaged in CSR were all important predictors of U.S. consumers\u27 intentions to patronize socially responsible apparel retail brands. Overall, the results of this study confirm applicability of the TRA and ECT in the context of consumers\u27 ethical decision making. Universalism values were found to be predictors of moral norms. Knowledge of environmental issues in the apparel industry and universalism values were found to influence consumers\u27 expectations of retail brands ethical behavior. The findings also revealed that only consumers\u27 moral norms predicted their attitudes towards patronizing apparel retail brands engaged in CSR. However, there was no significant relationship between knowledge of social and environmental issues and expectations of ethical behavior. Also, there were no significant differences in consumers\u27 patronage intentions based on gender, education or household income. An important theoretical contribution of this study is that it supports previous research that indicated extending the TRA and theory of planned behavior to include measures of values and moral norms in ethical context (Conner & Armitage, 1998; Manstead, 2000; Armitage & Conner, 2001). Findings from this study provide an understanding of the significant roles of universalism values and moral norms in consumers\u27 attitude formation, expectations and patronage intentions for apparel products. The results of this study present valuable insights for apparel retail brands engaged in CSR or planning to incorporate CSR policies in their corporate agenda. It is proposed that apparel retail brands should integrate CSR related information in their strategic marketing activities to increase consumer awareness of its socially responsible business practices, which in turn may enhance brand image

How Do Employees Perceive Corporate Responsibility? Development and Validation of a Multidimensional Corporate Stakeholder Responsibility Scale

Recent research on the microfoundations of corporate social responsibility (CSR) has highlighted the need for improved measures to evaluate how stakeholders perceive and subsequently react to CSR initiatives. Drawing on stakeholder theory and data from five samples of employees (N = 3,772), the authors develop and validate a new measure of corporate stakeholder responsibility (CStR), which refers to an organization’s context-specific actions and policies designed to enhance the welfare of various stakeholder groups by accounting for the triple bottom line of economic, social, and environmental performance; it is conceptualized as a superordinate, multidimensional construct. Results from exploratory factor analyses, first- and second-order confirmatory factor analyses, and structural equation modeling provide strong evidence of the convergent, discriminant, incremental, and criterion-related validities of the proposed CStR scale. Two-wave longitudinal studies further extend prior theory by demonstrating that the higher-order CStR construct relates positively and directly to organizational pride and perceived organizational support, as well as positively and indirectly to organizational identification, job satisfaction, and affective commitment, beyond the contribution of overall organizational justice, ethical climate, and prior measures of perceived CSR

Electricity generation and emissions reduction decisions under uncertainty : a general equilibrium analysis

Thesis (Ph. D.)--Massachusetts Institute of Technology, Engineering Systems Division, 2013.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Cataloged from student-submitted PDF version of thesis.Includes bibliographical references (pages 169-183).The electric power sector, which accounts for approximately 40% of U.S. carbon dioxide emissions, will be a critical component of any policy the U.S. government pursues to confront climate change. In the context of uncertainty in future policy limiting emissions and future technology costs, society faces the following question: What should the electricity mix we build in the next decade look like? We can continue to focus on conventional generation or invest in low-carbon technologies. There is no obvious answer without explicitly considering the risks created by uncertainty. This research investigates socially optimal near-term electricity investment decisions under uncertainty in future policy and technology costs. It employs a novel framework that models decision-making under uncertainty with learning in an economy-wide setting that can measure social welfare impacts. Specifically, a computable general equilibrium (CGE) model is formulated as a two-stage stochastic dynamic program focused on decisions in the electric power sector. The new model is applied to investigate a number of factors affecting optimal near-term electricity investments: (1) policy uncertainty, (2) expansion rate limits on low-carbon generation, (3) low-carbon technology cost uncertainty, (4) technological learning (i.e., near-term investment lowers the expected future technology cost), and (5) the inclusion of a safety valve in future policy which allows the emissions cap to be exceeded, but at a cost. In modeling decision-making under uncertainty, an optimal electricity investment hedging strategy is identified. Given the experimental design, the optimal hedging strategy reduces the expected policy costs by over 50% compared to a strategy derived using the expected value for the uncertain parameter; and by 12-400% compared to strategies developed under a perfect foresight or myopic framework. This research also shows that uncertainty has a cost, beyond the cost of meeting a policy. In the experimental design used here, uncertainty in the future policy increases the expected cost of policy by over 45%. If political consensus can be reached and the climate science uncertainties resolved, setting clear, long-term policies can minimize expected policy costs. In addition, this work contributes to the learning-by-doing literature by presenting a stochastic formulation of technological learning in which near-term investments in a technology affect the probability distribution of the future cost of that technology. Results using this formulation demonstrate that learning rates lower than those found in the literature can lead to significant additional near-term investment in low-carbon technology in order to lower the expected future cost of the technology in case a stringent policy is adopted.Ultimately, this dissertation demonstrates that near-term investments in low-carbon technologies should be greater than what would be justified to meet near-term goals alone. Near-term low-carbon investments can lower the expected cost of future policy by developing a less carbon-intensive electricity mix, spreading the burden of emissions reductions over time, helping to overcome technology expansion rate constraints, and reducing the expected future cost of low-carbon technologies-all of which provide future flexibility in meeting a policy. The additional near-term cost of low-carbon investments is justified by the future flexibility that such investments create. The value of this flexibility is only explicitly considered in the context of decision-making under uncertainty.by Jennifer Faye Morris.Ph.D

Nonparametric efficiency and productivity change measurement of banks with corporate social responsibilities : the case for Ghana

This thesis has twofold objectives. The first is to develop a framework based on the existing theory and method of Data Envelopment Analysis (DEA) for measuring performance of financial firms that have the dual goals of profit maximisation and Corporate Social Responsibilities (CSRs). The second is to examine the impact of banking regulatory reforms including bank ownership, specialisation, and capitalisation types on the average efficiency and frontier differences of banking subgroups. The objectives are achieved using the standard DEA, the metafrontier analysis and the global frontier differences (GFD). DEA can handle multidimensional inputs and outputs without specifying specific functional forms. CSR is conceptually justified and modelled as an additional output into the banking intermediation approach. Two DEA models, one with CSR and another without CSR are measured and compared. Parametric and nonparametric tests and regressions are utilised to support, empirically, the relevance of CSR in bank performance evaluation. Do foreign banks outperform private-domestic and state banks? Should banks diversify their products or focus in narrow range of products and services? Are listed banks more efficient than non-listed banks? The second part of the thesis contributes to the extant literature by answering these questions using the metafrontier analysis and the GFD to provide new evidence on the effect that the entry of foreign and private-domestic banks, universal banking and listing of banks on the stock market, have on bank performance. Banks are segmented into groups based on their bank-specific attributes and their average efficiencies and bestpractice differences compared. Relevant policy recommendations are drawn from the analysis for both the banking regulator and bank management. The final methodological contribution extends the GFD by defining a further decomposition of the global frontier shift, into components that indicate whether an observation is situated in a more or less favourable location in the production possibility set. Consequently, a four-factor “Newly-decomposed Malmquist productivity change index” is proposed. The index and its decompositions have potentially interesting policy implications, which are illustrated using the empirical data on Ghanaian banks. The index is in the spirit of the standard Malmquist index but the intuition is that some components can be used to draw conclusions about productivity changes for a whole population of firms whilst others determine whether individual firms are in favourable locations and/or moving towards locations that are more favourable over time. More importantly, arguably, a listed, universal or foreign bank can be located in a favourable position and move towards location that is more favourable by virtue of its bank-specific attributes or by contributing more towards CSR. These factors are explored and policy measures prescribed in the final contribution of the thesis

Accounting and Statistical Analyses for Sustainable Development

In this Open Access publication Claudia Lemke develops a comprehensive Multi-Level Sustainable Development Index (MLSDI) that is applicable to micro, meso, and macro objects by conducting methodological and empirical research. Multi-level comparability is crucial because the Sustainable Development Goals (SDGs) at macro level can only be achieved if micro and meso objects contribute. The author shows that a novel information-theoretic algorithm outperforms established multivariate statistical weighting methods such as the principal component analysis (PCA). Overcoming further methodological shortcomings of previous sustainable development indices, the MLSDI avoids misled managerial and political decision making