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The purpose of this paper is to highlight challenges for service firms communicating Environmental, Social and Governance (ESG) efforts to customers. Specifically, it focuses on the relationship between ESG metrics and reporting and customer perceptions of social innovativeness.

The empirical material comprises three years of data (2018–2020) covering more than 100 firms from three sources: (1) Social Innovation Index (Sii), which is collected as part of the American Innovation Index (Aii), (2) Bloomberg Sustainability Accounting Standards Board (SASB) ESG and (3) Datamaran.

ESG metrics and reporting do not suffice to explain customer perceptions of social innovativeness. Rather, a firm's industry plays the prominent role in affecting these perceptions where service firms are at a disadvantage as customers perceive services as less socially innovative compared to goods.

While ESG metrics and reporting provide important information for investors and regulators, they are not reflected in customers' perceptions of firms' social innovativeness, and services are at a disadvantage relative to goods. Therefore, services researchers and managers must advance their knowledge regarding how to better link ESG metrics and report to customers' perceptions.

The paper offers a first large-scale, cross-industry investigation of how ESG metrics and reporting impact customer perceptions of social innovativeness, leading to a research agenda on communication of ESG.

In this case students must ascertain what financial ratios they recommend the company focus on and they must also decide how best to communicate, explain, and bring to life those metrics so that the company's cadre of non-financial middle managers can most easily understand the significance of, and internalize the insights from, those ratios. Embedded in this task, students must: (1) understand the nature of the company insights afforded by each of the potential financial metrics presented; (2) make a judgment as to which subset of financial metrics is (a) most applicable to a group of non- financial middle managers and (b) most representative of bankers' and shareholders' interests; and (3) develop a plan for communicating to a group of non-financial, middle managers the subset of financial metrics they have selected.

The purpose of this paper is to standardised four-step flexibility assessment methodology for evaluating the available electrical load reduction or increase a building can provide in response to a signal from an aggregator or grid operator.

The four steps in the methodology consist of Step 1: systems, loads, storage and generation identification; Step 2: flexibility characterisation; Step 3: scenario modelling; and Step 4: key performance indicator (KPI) label.

A detailed case study for one building, validated through on-site experiments, verified the feasibility and accuracy of the approach.

The results were benchmarked against available demonstration studies but could benefit from the future development of standardised benchmarks.

The ease of implementation enables building operators to quickly and cost effectively evaluate the flexibility of their building. By clearly defining the flexibility range, the KPI label enables contract negotiation between stakeholders for demand side services. It may also be applicable as a smart readiness indicator.

The novel KPI label has the capability to operationalise the concept of building flexibility to a wider spectrum of society, enabling smart grid demand response roll-out to residential and small commercial customers.

This paper fulfils an identified need for an early stage flexibility assessment which explicitly includes source selection that can be implemented in an offline manner without the need for extensive real-time data acquisition, ICT platforms or additional metre and sensor installations.

In mature global business-to-business (B2B) product markets, management of external sales channels, governed by contractual relationships, is a key determinant of business performance. However, existing sales channel management literature lacks focus on contractual governance and reseller management success. The purpose of the study is to systematically review different governance theories in relation to sales channel management and to show which factors are the most influential in making or keeping external sales channels effective.

A case study on a large B2B information and communication technology (ICT) company is used to reflect on the way the different theoretical governance perspectives explain sales channel management success. Interviews and mini-questionnaires were used to collect data.

Expressions of interdependence and equality alongside persevered personal relationships are important in managing daily business activities and in avoiding bad will at the reseller’s grass-root level. Future-oriented planning, long-term-oriented support and jointly set incentive systems are important for reseller management. Degree of professional management sets resellers apart through shifts in power balance.

A multi-theory governance perspective offers a holistic view over reseller management and provides a comprehensive view over different sales channel management issues and their relative importance.

The findings highlight the importance of long-term orientation and cooperation in setting up a reseller management system to gain and nurture distributors’ trust and commitment towards the manufacturer.

The study is the first to comprehensively use governance perspective in studying reseller management.

Despite the availability of many metrics and tools for marketing performance measurement, the way in which firms use their marketing metrics remains underexplored. This study aims to address this gap by empirically establishing the differing effects of the diagnostic and interactive uses of marketing metrics on firms’ market-sensing capability, contingent on competitive intensity and focus on market-related metrics.

This study builds on survey data collected from 210 Irish-based firms, complemented by 21 in-depth interviews with business managers. Survey data are analysed using regression analysis.

This study finds that firms using marketing metrics interactively to communicate organizational focus are better able to sense their markets, especially under high competition. The authors observe a positive impact of the interactive use of metrics on market-sensing capability, but a U-shaped impact of their diagnostic use, the magnitudes of which further depend on competitive intensity and firms’ focus on market-related metrics.

This study provides a nuanced view of marketing performance measurement (MPM) practices within firms, particularly focussing on diagnostic versus interactive uses of marketing metrics. It also sheds further light on how two diverse uses of marketing metrics – diagnostic and interactive uses – influence a firm’s market-sensing capability. Moreover, the identification of boundary conditions also contributes to the discussion of contextuality in MPM, highlighting the importance of aligning a firm’s uses of marketing metrics with its business environment.

This study provides novel insights into how diverse uses of marketing metrics may benefit firms. The differing effects of diagnostic and interactive uses of marketing metrics on market sensing highlight a primary need for developing the latter and for using the former only with caution. It establishes that all firms would equally benefit from an interactive use of marketing metrics that is pivotal to improving their ability to anticipate, detect and sense market changes.

This study provides novel understanding of the role of marketing metric uses in firms’ market-sensing capability and contributes to the discussion of contextuality in marketing performance measurement. It highlights the importance of aligning a firm’s use of marketing metrics with its business environment.

Using metrics to communicate HR’s value to an organization is critical to the perception of HR as a valuable resource. What many HR professionals miss is that how those metrics are used in making a business case is just as important as having metrics themselves.

The purpose of this paper is to identify energy efficiency metrics that can be used by IT managers to measure and maintain the implementation of cost savings and green initiatives in data centers.

The paper looks at the background of the problem and explores the reasons why energy savings in the data center are an important issue. Included are interviews and survey results from IT professionals serving at four unique organizations. A model of the measurable components of a data center is created to provide a framework for organizing metrics and communicating results throughout the corporation. The strengths and weaknesses of two of the most common data center metrics, PUE and DCP, are examined closely.

The paper concludes with future metric recommendations and a proposed credit‐based system that could be applied to encourage closer management of these metrics.

The metric recommendations can be used by IT managers resulting in energy efficiency improvements in their data centers.

The paper provides a good comprehension of multiple approaches and makes recommendations for a platform metric that can be further developed and adopted as a standard.

The purposes of this paper are to: (1) characterize farmers’ market manager and vendor perceptions of the economic, social and environmental impact markets have on their local communities; and (2) how those impacts are tracked and communicated to market actors and the local community.

Twenty-nine semistructured interviews were conducted with market managers and vendors across four farmers’ markets within Michigan. The interviews were coded and analyzed using thematic analysis.

Managers and vendors report economic and social and environmental benefits associated with the presence of a farmers' market, consistent with the existing literature. Metrics are tracked to estimate market impact, particularly economic and social benefits. Market managers reported uncertainty about how best to use data internally, and there are gaps in communicating market impacts with vendors. Most data are used for external reporting, to statewide organizations or for grant evaluation. Respondents reported data fatigue and unwillingness among vendors to share personal business information due to concerns about privacy relative to the perceived benefits of sharing data.

Additional resources are needed for markets, specifically market managers, to better utilize the data they collect for internal versus external purposes.

Metric collection and reporting are a nascent development among markets. Understanding how market actors are utilizing these tools will provide guidance to improve future efforts at impact measurement.

This study addresses the need for a theory-guided, rich, descriptive account of research data repositories' (RDRs) understanding of data quality and the structures of their data quality assurance (DQA) activities. Its findings can help develop operational DQA models and best practice guides and identify opportunities for innovation in the DQA activities.

The study analyzed 122 data repositories' applications for the Core Trustworthy Data Repositories, interview transcripts of 32 curators and repository managers and data curation-related webpages of their repository websites. The combined dataset represented 146 unique RDRs. The study was guided by a theoretical framework comprising activity theory and an information quality evaluation framework.

The study provided a theory-based examination of the DQA practices of RDRs summarized as a conceptual model. The authors identified three DQA activities: evaluation, intervention and communication and their structures, including activity motivations, roles played and mediating tools and rules and standards. When defining data quality, study participants went beyond the traditional definition of data quality and referenced seven facets of ethical and effective information systems in addition to data quality. Furthermore, the participants and RDRs referenced 13 dimensions in their DQA models. The study revealed that DQA activities were prioritized by data value, level of quality, available expertise, cost and funding incentives.

The study's findings can inform the design and construction of digital research data curation infrastructure components on university campuses that aim to provide access not just to big data but trustworthy data. Communities of practice focused on repositories and archives could consider adding FAIR operationalizations, extensions and metrics focused on data quality. The availability of such metrics and associated measurements can help reusers determine whether they can trust and reuse a particular dataset. The findings of this study can help to develop such data quality assessment metrics and intervention strategies in a sound and systematic way.

To the best of the authors' knowledge, this paper is the first data quality theory guided examination of DQA practices in RDRs.