Rethinking How We Measure Corporate Social Responsibility

10617765806_b7f4f4ca12_z[We’re pleased to welcome Gunther Capelle-Blancard. Gunther recently published an article in Business & Society with co-author Aurélien Petit entitled “The Weighting of CSR Dimensions: One Size Does Not Fit All.”]

Companies could develop eco-friendly products or support social programs, and meanwhile damage the environment or experiment governance failures. Corporate Social Responsibility is multidimensional. Often, though, responsible investors (and customers) are interested in synthetic rankings that sum up the ESG (Environmental, Social and corporate Governance) scores.  Such composite scores raise fundamental questions which, surprisingly, are widely overlooked by academics and practitioners.

If the question of fungibility (“do good actions compensate bad ones?”) is essential and has been discussed in the literature, this article focuses on commensurability (the “apples and oranges” problem). For instance, Oil & Gas companies are mostly criticized on environmental issues, while corporate governance is the main stake for Banks. Overall ratings that sum equally environmental, social and corporate governance marks would not reflect the sectors’ concerns. One size does not fit all.

We develop a new method of CSR rating, based on news disclosed by the media and nongovernmental organizations. Thanks to the Covalence EthicalQuote database, we BAS Coveranalyze more than 70,000 positive or negative ESG news, regarding the world’s largest companies. Our results suggest that rating agencies and previous academic research underweight the environment and corporate governance. Mostly, our method allows fitting the ratings to the sectors’ specific stakes. It can be used to assess Corporate Social Performance better.

The abstract for the paper:

Although the concept of corporate social responsibility (CSR) is fundamentally multidimensional, most studies use composite scores to assess corporate social performance (CSP). How relevant are such composite scores? How the CSR dimensions are weighted? Should the weighting scheme be the same across sectors? This article proposes an original weighting scheme of CSR strengths and concerns, at the sector level, which is proportional to media and nongovernmental organizations (NGOs) scrutiny. The authors show that previous CSP assessments underweight environmental and corporate governance concerns. Moreover, findings suggest that firms that are exposed to the closest scrutiny are usually criticized on one single dimension: for instance, banks for bad corporate governance, and basic-resource firms for environmental damage. Composite scores based on equal weights hence misrepresent CSP and the difference in CSR between sectors.

You can read “The Weighting of CSR Dimensions: One Size Does Not Fit All” from Business & Society free for the next two weeks by clicking here. Want to know all about the latest research from Business & SocietyClick here to sign up for e-alerts!

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*Highrise image credited to Sonny Abesamis (CC)

gunther_IMG_20150922_164249_b41bfe265c.jpgGunther Capelle-Blancard (PhD, University of Paris 1) is professor of economics at the University of Paris 1 Panthéon-Sorbonne and research fellow at the Centre d’Economie de la Sorbonne and Labex RéFi (Regulation financière). His research examines socially responsible investment, corporate social performance, and financial market regulation. His articles have appeared in such journals as Business Ethics: A European Review, European Financial Management Journal, Journal of Environmental Economics and Management, and Journal of Investing.

Aurélien Petit

Aurélien Petit (PhD, University of Paris 1) is research fellow at the Centre d’Economie de la Sorbonne. His research interests focus on corporate social responsibility and information disclosure strategies.

Why Would You Choose to Revisit a Dissatisfying Restaurant?

02JSR13_Covers.inddWe’re pleased to welcome Dr. Gabriele Pizzi of the University of Bologna. Dr. Pizzi recently collaborated with Gian Luca Marzocchi, Chiara Orsingher and Alessandra Zammit on their paper published in the Journal of Service Research entitled “The Temporal Construal of Customer Satisfaction.”

A dirty plate at the restaurant where we were having a research meeting at lunch inspired the intuition behind the research idea portrayed in this work. Just upon the exit, we were so dissatisfied that we promised we would never come back to that restaurant. Interestingly, when choosing a restaurant some months later during another research meeting, one of us proposed THAT restaurant. After all, the atmosphere was pleasing and the room was quiet so that we could discuss about our research plans without being bothered. We started wondering why the evaluation of the restaurant had changed over time. Someone proposed that the details of the experience were forgotten: however, all of us perfectly remembered about the dirty plate. Presumably, over time the relevance of the dirty plate had decreased in our evaluations.

We explain this phenomenon through the lenses of Construal Level Theory, which posits that that individuals generate different mental representation of events that are placed at distinct points in the near rather than the distant future. For example, organizing a party for the next month is construed at a high level of abstraction, in terms of “having fun,” and “seeing friends.” A few days before the party, however, the same event is construed at a low level of abstraction, such as “buying food and drinks,” and “decorating the house.”

We show that construal mechanisms are activated also to reconstruct and evaluate past experiences. Basing on the results of two experiments and a field study, we find that the importance of the attributes driving satisfaction shifts over time, with concrete attributes of the experience ranking higher than abstract attributes in the evaluation of near-past experiences. The opposite happens for the evaluation of distant-past experiences. In addition, we show that overall satisfaction judgments shift over time as a function of the different performances of abstract and concrete attributes. Customers are more satisfied with a service experience featuring concrete positive and abstract negative attributes when they evaluate it in the near past. Conversely, they are more satisfied with a service experience featuring abstract positive and concrete negative attributes when they evaluate the experience in the distant past.

Our findings have several important implications for designing satisfaction surveys more effectively. We advise companies to design surveys that measure satisfaction repeatedly to obtain the whole spectrum of evaluations. Focusing on the so-called online evaluations (i.e., evaluation collected immediately after the service experience is over) may be misleading: Online satisfaction surveys might overemphasize (underemphasize) the impact of low-level negative (high-level positive) attributes on the overall satisfaction judgment. Additionally, the content and the wording of satisfaction surveys are relevant: if the content of the questionnaire and the construal level of the past experience are not correctly paired, it may be difficult to find an exhaustive explanation for the determinants of overall customer satisfaction/dissatisfaction.

In summary, our research shows that when consumers evaluate a service experience that has happened in the near-past (e.g., two days earlier) they rely on concrete service attributes, but they rely on abstract attributes when they evaluate the same experience in the distant-past (e.g., two months earlier). This is why a concrete attribute such as a dirty plate might have been discarded from our distant past satisfaction judgments about the restaurant. Eventually, we came back to that restaurant and we received an unexpected gift at the end of our lunch. But that’s another research project.

You can read “The Temporal Construal of Customer Satisfaction” from Journal of Service Research by clicking here. Want to have all the latest news and research from Journal of Service Research sent directly to your inbox? Click here to sign up for e-alerts.


pizziGabriele Pizzi is an Assistant Professor of marketing at the University of Bologna. His research interests include customer satisfaction measurement, intertemporal choices, and inventory management. His work has appeared in the Journal of Retailing, Journal of Behavioral Decision Making, and the Journal of Economic Psychology.

gianGian Luca Marzocchi is a Professor of marketing and consumer behavior at the University of Bologna. His research specialties include customer satisfaction modeling, waiting perception in service settings, intertemporal choice, and the interplay between brand loyalty and community identification in brand communities. His refereed works have appeared in Journal of Applied Psychology, Journal of Economic Psychology, Psychology and Marketing, International Journal of Service Industry Management, Entrepreneurship Theory and Practice, among others.

chiaraChiara Orsingher is an Associate Professor of marketing at the University of Bologna. Her research interests include service recovery and complaint handling, meta-analysis, and referral reward programs. Her work has appeared in the Journal of Academy of Marketing Science, Journal of Service Research, Psychology & Marketing and the International Journal of Service Industry Management.

zammitAlessandra Zammit is an Assistant Professor of marketing at the University of Bologna. Her research interests include context effects, social influence, self-customization decisions and identity based consumption. Her work has appeared in the Journal of Consumer Research and in the Service Industries Journal.

When Designing Multiple Channels, Mirror Attributes Matter

[We’re pleased to welcome Maik Hammerschmidt of the University of Göttingen in Germany. Dr. Hammerschmidt recently published an article in the OnlineFirst section of Journal of Service Research with Tomas Falk of Aalto University School of Business in Finland and Bert Weijters of Ghent University in Belgium entitled “Channels in the Mirror: An Alignable Model for Assessing Customer Satisfaction in Concurrent Channel Systems.”

Contrary to popular belief, customers who are shopping do not seem to change 02JSR13_Covers.inddmindsets when switching between offline and online channels. This finding—implying that the attributes consumers use for evaluating offline and online channels mirror each other—represents the punch line in our a recent study published in the OnlineFirst section of Journal of Service Research.

In our paper, we introduce the 5C model of customer satisfaction, which shows that five “mirror” features are mainly responsible for customer satisfaction in multichannel environments. Those channel features that have corresponding attributes in the counterpart channel should be the focus of designing parallel routes to market. The five “Cs” of satisfaction relate to choice (assortment breadth and depth), charge (availability of fair prices), convenience (efficiency of the purchase process), confidence (security of transactions), and care (assurance of promised quality).

The study shows that the 5C model improves on existing approaches for measuring multichannel performance because it lets the firm keep an eye on both offline and online satisfaction in a consistent manner. A unified view of channels helps marketers monitor the performance of basic shopping attributes in both traditional and digital formats. Only a monitoring instrument that uses similar measures for all channels will allow managers to meaningfully benchmark channel-specific satisfaction scores.

We see a further major benefit of the 5C metric in its direct linkage to the proportionate allocation rule. A channel’s investment should match its unexploited satisfaction potential. Therefore, managers ideally invest greater marketing effort in the channel indicating lower absolute satisfaction levels.

Interestingly, the 5C model is not limited to between-channel comparisons but can also be used to optimize within-channel decisions. For example, if convenience is more important for online satisfaction than price, firms should invest more in ensuring easy and efficient online transactions and skip the frequent online price promotions. Given the findings, we feel that while managing shared features of channels is a good starting point, channel-unique features need attention, too, particularly when each step of the shopping process involves a specialized channel or when expert customers are the target group.

You can read “Channels in the Mirror: An Alignable Model for Assessing Customer Satisfaction in Concurrent Channel Systems” from Journal of Service Research for free by clicking here. Want to know about all the latest news and research from Journal of Service Research? Click here to sign up for e-alerts!


Maik HammerschmidtMaik Hammerschmidt (PhD, University of Mannheim) is a chaired professor of marketing and innovation management at the Georg August University Göttingen, Germany. His research focuses on improving the financial performance of marketing activities, particularly in the areas of service marketing, multichannel management, social media marketing and CSR initiatives. He has coauthored and coedited four books on marketing performance and marketing efficiency and has published in journals such as Journal of Marketing, Journal of the Academy of Marketing Science, Journal of Service Research, and Journal of Business Research. He has received numerous awards for his academic achievements, including an Overall Best Paper Award of the American Marketing Association.

Tomas FalkTomas Falk (PhD, University of Mannheim) is an associate professor of marketing at Aalto University School of Business, Finland, and an adjunct professor of marketing at EBS Business School, Germany. His research interest and expertise focus on service channel management, service quality management, self-service technologies, and service employee behavior. His research has been published in journals such as Journal of Marketing, Journal of the Academy of Marketing Science, Journal of Service Research, and Journal of Business Research. He has won several research awards, including an Overall Best Paper Award of the American Marketing Association.

Bert WeijtersBert Weijters (PhD, Ghent University) is an assistant professor of consumer research at Ghent University, Belgium. His research focuses on survey methods in consumer research and has been published in leading journals in business and psychology, including Journal of Marketing Research, Journal of Consumer Research, Journal of the Academy of Marketing Science, Journal of Service Research, International Journal of Research in Marketing, Applied Psychological Measurement, and Psychological Methods.

Marcia Simmering on the Detection of Common Method Variance

[We’re pleased to welcome Marcia Simmering of Louisiana Tech University. Dr. Simmering recently published an article in Organizational Research Methods with Christie M. Fuller, Hettie A. Richardson, Yasemin Ocal, and Guclu M. Atinc entitled “Marker Variable Choice, Reporting, and Interpretation in the Detection of Common Method Variance: A Review and Demonstration.”]

  • What inspired you to be interested in this topic?

07ORM13_Covers.inddAfter the publication of my earlier piece on common method variance (Richardson, Simmering, Sturman, 2009 in ORM), where we found that marker variables could be potentially useful in detecting method variance, I kept getting questions from other researchers about what marker variables they should use in their own studies. I didn’t always have an answer, because the appropriateness of a marker variable depends on the study variables. So, I worked with a team of co-authors from different business disciplines on the current paper to find good marker variables in a variety of studies. As we all read articles using marker variables, we found so much variation in how they were used, and we learned that many had not been chosen or implemented properly. So, my coauthors and I decided to give an overview of how these techniques have been used (and misused). We took it a step further and tried to find out what these marker variables are really measuring and whether they’re measuring something different from presumed causes of common method variance (CMV), like social desirability and affectivity.

  • Were there findings that were surprising to you?

Yes! I would say that most of what we found in both studies surprised us. In Study 1 (the review of marker variable use), I didn’t expect so many authors to choose marker variables that really couldn’t properly capture CMV. And, I was surprised at how little journal space was given to tests of CMV. In Study 2, we didn’t know what we would find about what marker variables might detect in comparison to presumed causes of CMV, but we were still surprised to find that one added measure (either marker or presumed cause) is likely not enough to reasonably detect CMV and that multiple marker and CMV-cause variables in one study give much more information.

  • How do you see this study influencing future research and/or practice?

We hope that other researchers can find this article helpful in choosing appropriate marker variables and analyzing them in a way that can reasonably detect CMV. This is easier said than done, because a good marker variable is often chosen before data collection, and perhaps this article can influence more authors to do that. But, we hope, too, that reviewers gain some knowledge about how these techniques can be used to detect CMV. And, our ultimate goal is that this work can get us a little bit closer to understanding the large, complex, and still ambiguous phenomenon of CMV in social science research.

You can read “Marker Variable Choice, Reporting, and Interpretation in the Detection of Common Method Variance: A Review and Demonstration” from Organizational Research Methods for free for the next two weeks by clicking here. Want to know about all the latest research like this from Organizational Research Methods? Click here to sign up for e-alerts!


marcia_dickersonMarcia J. Simmering is the Francis R. Mangham Endowed professor of Management and assistant dean of Undergraduate Programs in the College of Business at Louisiana Tech University. Her current research focuses on the methods topics of common method variance and control variables. Additionally, she has published research on feedback, compensation, and training.

Christie M. Fuller is Thomas O’Kelly-Mitchener associate professor of Computer Information Systems at Louisiana Tech University. Her research in deception and decision support systems has been published in Decision Support Systems, Expert Systems with Applications, IEEE Transactions on Professional Communication, along with other journals and conference proceedings.

Richardson-Hettie for profileHettie A. Richardson is an associate professor and Chair of the Department of Management, Entrepreneurship, and Leadership in the Neeley School of Business at Texas Christian University. Her methodological research interests focus on common method variance and other measurement-related issues. She also studies employee involvement, empowerment, and strategic human resource management.

Yasemin Ocal is an assistant professor of Marketing at Texas A&M University-Commerce. Her research focuses on response rate and response bias in marketing research and has appeared in journals such as Journal of Leadership and Organizational Studies and numerous international conferences, including organization of a survey response rate issues session in World Marketing Congress of the Academy of Marketing Science.

atnicGuclu M. Atinc is an assistant professor of Management at Texas A&M University-Commerce. His current research addresses board composition, top management teams and ownership structures of young entrepreneurial firms, and research methods. Dr. Atinc’s research has appeared in journals such as Organizational Research Methods, Journal of Managerial Issues, and Journal of Leadership and Organizational Studies.

Will Airline Customers Buy Carbon Offsets?

cost-of-flying-1031410-m In an effort to help combat climate change, a number of corporations have turned to using carbon offsets to help rectify any damage done by their business to the environment. Companies such as United Airlines have even begun offering their customers the chance to purchase carbon offsets to counteract their flight. But how likely is it that customers will choose to purchase these carbon offsets? Authors Andy S. Choi, Brent W. Ritchie, and Kelly S. Fielding explored this topic in their article published in Journal of Travel Research entitled “A Mediation Model of Air Travelers’ Voluntary Climate Action.”

The abstract:

This study developed a behavioral model of intentions to purchase aviation carbon offsets, and tested the model through JTR_72ppiRGB_powerpointstructural equation models. The model draws on the established hierarchical models of human behavior to hypothesize relationships between general and specific attitudes as predictors of offsetting intentions. The New Ecological Paradigm scale, the theory of planned behavior and variables from past literature were employed to measure general environmental attitudes, intermediate beliefs, and behavior-specific attitudes and norms. The current research represents a first attempt to build a theoretical model that helps to understand the relationships between factors that determine whether people will purchase aviation carbon offsets. The results show that a more positive orientation toward the environment could be an important predictor of environmental intentions operating both directly on intentions as well as guiding beliefs that relate to intentions. Policy implications of the findings are discussed, encouraging greater voluntary climate action.

You can read “A Mediation Model of Air Travelers’ Voluntary Climate Action” from Journal of Travel Research for free for the next week by clicking here. Want to know about all the latest research like this from Journal of Travel Research? Click here to sign up for e-alerts!

The Search for Cross-level Interaction Effects: Fruitful or Futile?

[We’re pleased to welcome Herman Aguinis of Indiana University and Steven Andrew Culpepper of the University of Illinois at Urbana-Champaign. Drs. Aguinis and Culpepper recently collaborated on their article from Organizational Research Methods entitled “An Expanded Decision-Making Procedure for Examining Cross-Level Interaction Effects With Multilevel Modeling.”]

Researchers in organizational behavior, human resource management, 07ORM13_Covers.inddentrepreneurship, strategy, sociology, psychology, education, and many other fields now explicitly recognize that lower-level entities are usually nested within higher-level collectives. For example, employees are nested within jobs and teams, establishments within companies, and firms within industries. However, how do we know whether there is variability of a lower-level relationship across higher-order units? The answer to this question has important implications in terms of the appropriateness of using usual data-analytic techniques based on ordinary least squares regression, or whether a multilevel modeling approach should be used. Moreover, the presence of variability in lower-order relationships across higher-order units leads to an examination of potential contextual factors that may serve as moderators of such relationships. In addition, practitioners are particularly interested in such effects because they provide information on the contextual conditions and processes under which interventions focused on individuals (e.g., selection, leadership training, performance appraisal and management) result in more or less positive outcomes.

Our article which appears in Organizational Research Methods titled “An Expanded Decision Making Procedure for Examining Cross-level Interaction Effects with Multilevel Modeling” offers a new index to assess variability of lower-level relationships across higher-order processes and units. This new index is labeled intraclass correlation beta (i.e., ρ_β). We illustrate the computation of ρ_β using previously published articles and also a Monte Carlo study. Our results suggest that researchers contemplating the use of multilevel modeling, as well those who suspect nonindependence in their data structure, should expand the decision criteria for using multilevel approaches to include ρ_β. To facilitate this process, we offer illustrative data sets and the icc_beta R package for computing ρ_β in single and multiple-predictor situations and make them available through the Comprehensive R Archive Network (i.e., CRAN).

We are very excited about the potential of ρ_β to allow us to uncover the presence of variability in lower-order relationships across higher-order process and units and look forward to discoveries that can be made based on information provided by ρ_β. Moreover, ρ_β can also be used as an index of effect size and used to synthesize previously published research to understand which may be more or less fruitful research domains in which cross-level moderating effects may exist.

You can read “An Expanded Decision-Making Procedure for Examining Cross-Level Interaction Effects With Multilevel Modeling” from Organizational Research Methods free for the next week by clicking here. Want to know about all the latest research from Organizational Research Methods? Click here to sign up for e-alerts!


aguinis5Herman Aguinis (http://mypage.iu.edu/~haguinis) is the John F. Mee Chair of Management and Founding Director of the Institute for Global Organizational Effectiveness in the Kelley School of Business, Indiana University. His multi-disciplinary, multi-method, and multi-level research addresses human capital acquisition, development, and deployment, and research methods and analysis. He has published five books and more than 120 articles in refereed journals. He is a Fellow of the Academy of Management, former editor-in-chief of Organizational Research Methods, and received the 2012 Academy of Management Research Methods Division Distinguished Career Award for lifetime contributions.

Steven Andrew Culpepper (http://publish.illinois.edu/sculpepper/) is an assistant professor in the Department of Statistics at the University of Illinois at Urbana-Champaign. He completed a doctorate in educational psychology from the University of Minnesota in 2006. His research focuses on statistical methods in the social sciences and includes the development of new methodologies, evaluation of existing procedures, and application of novel statistical techniques to substantive questions in demography, education, management, and psychology.

Announcing the Winners of the 2014 Best Paper Award from Family Business Review!

trophy-189659-mWe’re pleased to congratulate Nava Michael-Tsabari, Rania Labaki, and Ramona Kay Zachary, winners of 2014 Best Paper Award from Family Business Review! Their award-winning article entitled “Toward the Cluster Model: The Family Firm’s Entrepreneurial Behavior Over Generations” appeared in the June 2014 issue of Family Business Review.

The abstract:

Building on a longitudinal case study, this article describes the entrepreneurial behavior of a FBR_C1_revised authors color.inddmultinational family firm over generations. The study inductively raises the theoretic level to fill gaps in the literature about the family role in entrepreneurial behavior and addresses the singular count of the two- and three-circle models. The data analysis shows that entrepreneurial behavior emerges not only in response to business challenges but also and predominantly to family challenges. The cluster model is suggested as a necessary extension of the circle models, positing the family as the relevant level of analysis when considering entrepreneurial behavior and introducing the distinction between organic and portfolio, core and peripheral firms.

You can read this article for free for the next 30 days by clicking here. You can also listen to an interview with Nava Michael-Tsabari and Karen Vinton, Assistant Editor of Family Business Review, about the study by clicking here. Want to know about all the latest research and announcements from Family Business Review? Click here to sign up for e-alerts!