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This study aims to provide and illustrate the application of a framework for conducting techno-economic analyses (TEA) of early-stage designs for net-zero water and energy, single-family homes that meet affordable housing criteria in diverse locations.

The framework is developed and applied in a case example of a TEA of four designs for achieving net zero-water and energy in an affordable home in Saint Lucie County, Florida.

Homes built and sold at current market prices, using combinations of well versus rainwater harvesting (RWH) systems and grid-tied versus hybrid solar photovoltaic (PV) systems, can meet affordable housing criteria for moderate-income families, when 30-year fixed-rate mortgages are at 2%–3%. As rates rise to 6%, unless battery costs drop by 40% and 60%, respectively, homes using hybrid solar PV systems combined with well versus RWH systems cease to meet affordable housing criteria. For studied water and electricity usage and 6% interest rates, only well and grid-tied solar PV systems provide water and electricity at costs below current public supply prices.

This article provides a highly adaptable framework for conducting TEAs in diverse locations for designs of individual net-zero water and energy affordable homes and whole subdivisions of such homes. The framework includes a new technique for sizing storage tanks for residential RWH systems and provides a foundation for future research at the intersection of affordable housing development and residential net-zero water and energy systems design.

Although accounting and reporting visualisations (i.e. graphs, maps and grids) are often used to veil organisations’ untransparent actions, these practices perform irrespectively of their ability to represent facts. In this research, the authors explore accounting and reporting visualisations beyond their persuasive and representational purpose.

By building on previous research on the rhetoric of visualisations, the authors illustrate how the design of accounting visualisations within integrated reports engages managers in a recursive process of knowledge construction, interrogation, reflection and speculation on what sustainable value creation means. The authors articulate the theoretical framework by developing a longitudinal field study in International Fashion Company, a medium-sized company operating in the fashion industry.

This research shows that accounting and reporting visualisations do not only contribute to creating unclear and often contradicting representations of organisations’ sustainable performance but, at the same time, “open up” and support managers’ unfolding search for “sustainable value” by reducing its unknown meaning into known and understandable categories. The inconsistencies and imperfections that accounting and reporting visualisations leave constitute the conditions of possibility for the interrogation of the unknown to happen in practice, thus augmenting managers’ questioning, reflections and speculation on what sustainable value means.

This study shows that accounting and reporting visualisations can represent good practices (the authors are not saying a “solution”) through which managers can re-appreciate the complexities of measuring and defining something that is intrinsically unknown and unknowable, especially in contexts where best practices have not yet consolidated into a norm. Topics such as climate change and sustainable development are out there and cannot be ignored, cannot be reduced through persuasive accounts and, therefore, need to be embraced.

This study aims to explore the spatial externalities of apartment vacancy rates on housing rent by considering multiple vacancy durations.

This research uses smart meter data to measure unobservable vacant houses. This study made a significant contribution by applying building-level smart meter data to housing market analysis. It examined whether vacancy duration significantly affected apartment rent and whether the relationship between apartment rent and vacancy rate differed depending on the level of housing rent.

The primary finding indicates that there is a significant negative correlation between apartment rent and vacancy duration. Considering the spatial externalities of apartment vacancy rates, the apartment vacancy rates of surrounding buildings did not show any statistical significance. Moreover, quantile regression results indicate that although the bottom 10% of apartment rent levels showed a negative correlation with all vacancy durations, the top 10% showed no statistical significance related to vacancies.

This study measures the extent of spatial externalities that can differentiate taxation based on housing vacancies.

The findings indicate that landlords have asymmetric information about their buildings compared with the surrounding buildings, and the extent to which price adjusts for long-term vacancies differs depending on the level of apartment rent.

This study aims to address the global food waste problem in restaurants by analyzing customer sales information provided by restaurant tickets to gain valuable insights into directing sales of perishable products and optimizing product purchases according to customer demand.

A system based on unsupervised machine learning (ML) data models was created to provide a simple and interpretable management tool. This system performs analysis based on two elements: first, it consolidates and visualizes mutual and nontrivial relationships between information features extracted from tickets using multicomponent analysis, bootstrap resampling and ML domain description. Second, it presents statistically relevant relationships in color-coded tables that provide food waste-related recommendations to restaurant managers.

The study identified relationships between products and customer sales in specific months. Other ticket elements have been related, such as products with days, hours or functional areas and products with products (cross-selling). Big data (BD) technology helped analyze restaurant tickets and obtain information on product sales behavior.

This study addresses food waste in restaurants using BD and unsupervised ML models. Despite limitations in ticket information and lack of product detail, it opens up research opportunities in relationship analysis, cross-selling, productivity and deep learning applications.

The value and originality of this work lie in the application of BD and unsupervised ML technologies to analyze restaurant tickets and obtain information on product sales behavior. Better sales projection can adjust product purchases to customer demand, reducing food waste and optimizing profits.

Rapidly increasing the proportion of installed wind power capacity with zero carbon emission characteristics will help adjust the energy structure and support the realization of carbon neutrality targets. The intermittency of wind resources and fluctuations in electricity demand has exacerbated the contradiction between power supply and demand. The time-of-use pricing and supply-side allocation of energy storage power stations will help “peak shaving and valley filling” and reduce the gap between power supply and demand. To this end, this paper constructs a decision-making model for the capacity investment of energy storage power stations under time-of-use pricing, which is intended to provide a reference for scientific decision-making on electricity prices and energy storage power station capacity.

Based on the research framework of time-of-use pricing, this paper constructs a profit-maximizing electricity price and capacity investment decision model of energy storage power station for flat pricing and time-of-use pricing respectively. In the process, this study considers the dual uncertain scenarios of intermittency of wind resources and random fluctuations in power demand.

(1) Investment in energy storage power stations is the optimal decision. Time-of-use pricing will reduce the optimal capacity of the energy storage power station. (2) The optimal capacity of the energy storage power station and optimal electricity price are related to factors such as the intermittency of wind resources, the unit investment cost, the price sensitivities of the demand, the proportion of time-of-use pricing and the thermal power price. (3) The carbon emission level is affected by the intermittency of wind resources, price sensitivities of the demand and the proportion of time-of-use pricing. Incentive policies can always reduce carbon emission levels.

This paper creatively introduced the research framework of time-of-use pricing into the capacity decision-making of energy storage power stations, and considering the influence of wind power intermittentness and power demand fluctuations, constructed the capacity investment decision model of energy storage power stations under different pricing methods, and compared the impact of pricing methods on optimal energy storage power station capacity and carbon emissions.

1. Electricity pricing and capacity of energy storage power stations in an uncertain electricity market.

2. Investment strategy of energy storage power stations on the supply side of wind power generators.

3. Impact of pricing method on the investment decisions of energy storage power stations.

4. Impact of pricing method, energy storage investment and incentive policies on carbon emissions.

5. A two-stage wind power supply chain including energy storage power stations.

Electricity pricing and capacity of energy storage power stations in an uncertain electricity market.

Investment strategy of energy storage power stations on the supply side of wind power generators.

Impact of pricing method on the investment decisions of energy storage power stations.

Impact of pricing method, energy storage investment and incentive policies on carbon emissions.

A two-stage wind power supply chain including energy storage power stations.

This paper aims to explore current trends in how companies disclose climate-related risks and opportunities in their financial statements. As part of the authors’ analysis, they examine: whether forward-looking assumptions and judgements are typically considered in reporting climate-related risks/opportunities; whether there are differences in the reporting practices of firms in carbon-intensive industries versus non-carbon-intensive industries; and whether negative media reports have an influence on the levels of disclosure a firm makes.

The authors chose content analysis as their methodology and examined the financial statements published by firms listed on the UK’s FTSE 100 between 2016 and 2020. This analysis is framed by Suchman’s three dimensions of legitimacy, being pragmatic, cognitive and moral.

Climate-related disclosures in the notes and financial accounts of these firms did increase over the period. Yet, overall, the level the disclosures was inadequate and the quality was inconsistent. From this, the authors conclude that pragmatic legitimacy is not a particularly strong driving factor in compelling organisations to disclose climate-related information. The firms in carbon-intensive industries do provide greater levels of disclosure, including both qualitative and quantitative (monetary) content, which is consistent with cognitive legitimacy. However, from a moral legitimacy perspective, this study finds that firms did not adapt responsively to negative media coverage as a way of reflecting their accountability to broader public norms and values. Overall, this analysis suggests that regulatory enforcement and a systematic reporting framework with adequate guidance is going to be critical to developing transparent climate-related reporting in future.

This paper contributes to existing studies on climate-related disclosures, which have mainly examined the ‘front-half’ of annual reports. Conversely, this study aims to shed light on these practices in the “back-half” of these reports, exploring the underlying reasons for reporting climate-related risks and opportunities in financial accounts. The authors’ insights into the current disclosure practices make a theoretical contribution to the literature. Practitioners can also draw on these insights to improve how they report on climate-related risks and opportunities in their financial statements.

The ongoing paradigm shift in the energy sector holds paramount implications for the realization of the sustainable development goals, encompassing critical domains such as resource optimization, environmental stewardship and workforce opportunities. Concurrently, this transformative trajectory within the power sector possesses a dual-edged nature; it may ameliorate certain challenges while accentuating others. In light of the burgeoning research stream on open innovation, this study aims to examine the intricate dynamics of knowledge-based industry-university-research networking, with an overarching objective to elucidate and calibrate the equilibrium of ambidextrous innovation within power systems.

The authors scrutinize the role of different innovation organizations in three innovation models: ambidextrous, exploitative and exploratory, and use a multiobjective decision analysis method-entropy weight TOPSIS. The research was conducted within the sphere of the power industry, and the authors mined data from the widely used PatSnap database.

Results show that the breadth of knowledge search and the strength of an organization’s direct relationships are crucial for ambidextrous innovation, with research institutions having the highest impact. In contrast, for exploitative innovation, depth of knowledge search, the number of R&D patents and the number of innovative products are paramount, with universities playing the most significant role. For exploratory innovation, the depth of knowledge search and the quality of two-mode network relations are vital, with research institutions yielding the best effect. Regional analysis reveals Beijing as the primary hub for ambidextrous and exploratory innovation organizations, while Jiangsu leads for exploitative innovation.

The study offers valuable implications to cope with the dynamic state of ambidextrous innovation performance of the entire power system. In light of the findings, the dynamic state of ambidextrous innovation performance within the power system can be adeptly managed. By emphasizing a balance between exploratory and exploitative strategies, stakeholders are better positioned to respond to evolving challenges and opportunities. Thus, the study offers pivotal guidance to ensure sustained adaptability and growth in the power sector’s innovation landscape.

The primary originality is to extend and refine the theoretical understanding of ambidextrous innovation within power systems. By integrating several theoretical frameworks, including social network theory, knowledge-based theory and resource-based theory, the authors enrich the theoretical landscape of power system ambidextrous innovation. Also, this inclusive examination of two-mode network structures, including the interplay between knowledge and cooperation networks, unveils the intricate interdependencies between these networks and the ambidextrous innovation of power systems. This approach significantly widens the theoretical parameters of innovation network research.

This paper aims to introduce the experience-dominant (Ex-D) logic model, which synthesizes the creation, perceptions and outcomes of Ex-D logic. It is designed to offer valuable insights for strategic managerial applications and future research directions.

Employing a qualitative approach by using eight selected product launch events from reviewed 100 event videos and 55 in-depth interviews with industrial managers to develop an Ex-D logic model, and data were coded and analysed via NVivo.

Results show that the firm’s Ex-D logic is operationalized as the mentalizing of the three types of customer needs (service competence, hedonic excitations and meaning making), the materializing of three types of customer experiences and customer journeys (service experience, hedonic experience and brand experience) and the moderating of three types of customer values (service values, hedonic values and brand values).

This study has implications for adding new insights into existing theory on dominant logic and customer experience management and also offers actionable recommendations for managerial applications.

This study sheds light on the importance of Ex-D logic from a strategic point of view and provides an organic view of the firm. It distinguishes firm perspective from customer perspective, firm experience from customer experience and firm journey from consumer journey.

This paper aims to help understand how community-based social entrepreneurs experience world-class “performance excellence” models and to explore the core values that enable social enterprises to become high-performance organizations.

Underpinned by Mindsponge processes, the proposed conceptual framework critiques the Baldrige criteria for performance excellence (BCPE) model in a global south context. The mixed-methods study fosters an in-depth analysis. First, it validates the BCPE mechanism in community-based social enterprises (CBSEs) before identifying the significant core values and concepts of BCPE that influence CBSEs to achieve high performance.

The BCPE, adapted from global north corporate principles and applied at a community level, can significantly develop global south organization performance excellence. Five core values and concepts from the 11 fundamental beliefs in driving performance excellence were found to support performance excellence in CBSE management. These values and concepts are “customer-focused excellence,” “social responsibility,” “systems perspective,” “visionary leadership” and “focus on success.”

First, factors influencing performance excellence are not limited to the core values elements discussed. Future research may clarify factors extracted from the “Process” category of BCPE to explore further how CBSEs can enhance their performance in a different formation path. Second, this study only considered the Thai-Phuan community in Pho Tak village, Nong Khai, Thailand, to represent as a single case study. However, different, clustered or contrasting CBSEs in other regions remain open for further exploration to enrich the knowledge of “performance excellence” in a community organization. Finally, a longitudinal study would be a welcome addition.

The following must be considered. First is setting a clear direction: the organization’s vision and mission, by purposeful design, should ensure that CBSE managers are leading by example and demonstrating the importance of social and environmental value creation. Second is developing institutional culture: fundamental core values focused predominantly on “customer-focused excellence” and “social responsibility” encourage collaboration by “working together to drive success”. Third is developing integrated management system: CBSEs need to ensure that the management systems can collaborate and complement each component to create performance excellence. Fourth is creating a learning organization: CBSEs need to create a culture of continuous learning through data collection, measurement, analysis and modification.

This study clarifies that the implementation of BCPE is crucial to the establishment of performance excellence at both macro- and micro-level organizations. According to the Malcolm Baldrige National Quality Award, the fundamental drivers of BCPE are the same for all types of organizations and in all sectors, whether in the private sector, education, health care or government (Blazey and Grizzell, 2021). By applying the Baldrige excellence model at the community level, this study found that CBSE can similarly strive for excellence and improved performance. This can lead to strengthened services, increased productivity and enhanced quality of life for the community.

This study provides a novel viewpoint on the Baldrige paradigm. Expressly, BCPE is compatible with global south community-based organizations to enhance performance excellence. Its essential contribution demonstrates that Baldrige model concepts are more widespread within smaller and underdeveloped territories than imagined. The recent (post-study) inclusion of “Community” as an independent sector in the Malcolm Baldrige National Quality Awards validates the research findings and recommendations proposed by this study.