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environmental performance. The findings of this empirical study pro- vide in-depth insights, which so far were only rarely presented in liter- ature. The article is structured to present the conceptual background of the research, then outline the research design and a presentation of the most important findings. We then delve into their implications with the discussion section and articulation of our general conclusions.
opportunities, carrying out actions, and monitoring the development on various fronts makes data-informed operations highly attractive in conjunction with organizations' work toward ambitious objectives they have set for themselves in relation to environmental sustainabil- ity, which address climate-change mitigation, circular economy, and biodiversity protection. For companies, the use of data offers particu- lar value for bringing environmental considerations into strategic and operative decision-making across a broad span of business functions, from product design to supply-chain management (de Sousa et al., 2019; Langley, 2022). In this connection, a body of data that covers diverse aspects of business activities and of product and service life cycles, including related environmental impacts, can yield knowledge for environmental sustainability. Variety of data could support businesses in their envi- ronmental efforts by illuminating multiple aspects of those life cycles and the related material flows and emissions, such that they can bet- ter assess environmental impacts and identify improvement opportu- nities (Nascimento et al., 2019; Tseng et al., 2018). In addition, data that reveal patterns in human behavior and needs could facilitate efforts to pinpoint opportunities for sustainable consumption, sound procurement choices, and new business models, while also providing technical input on the systems' performance that may aid in systemic improvements (Gupta et al., 2021; Luoma et al., 2021). Possible data sources range from companies' internal processes to external supply- chain partners and customers (Hartmann, 2016; Ranta et al., 2021). New, better means of accessing and applying environment-related data are being developed constantly. For instance, smart algorithms, connected devices, and Big Data can support resource- and energy- efficient production and consumption (Bohnsack et al., 2022); block- chain technologies serve tracking of materials' path through supply chains; waste-to-resource marketplaces may be established; and digi- tal twins and digital product passports assist in tracing product life cycles. Creating customer value – with data's potentially crucial contribu- tion to this – is a prerequisite for business success (Flint et al., 1997; Graf & Maas, 2008; Porter, 1996). Robert Woodruff (1997, p. 142) defines customer value as the “ customer's perceived preference for and evaluation of those product attributes, attribute performance, and consequences arising from use that facilitate (or block) achieving the customer's goals and purposes in use situations. ” Which attributes, consequences, and goals/purposes are desired gets affected by the product-use situation and can change over time. For instance, users' accumulated experiences, perceptions, preferences, and evaluations (both individual-level and social) affect value creation (Helkkula et al., 2012; Woodruff, 1997). Also, customers assess value relative to their own resources and processes, and they consider resources' inte- gration and sharing between providers and customers (Rintamäki & Saarijärvi, 2021). This factor is especially topical in the case of data: the value creation is a dynamic process (Grönroos, 2008; Tzokas & Saren, 1999) wherein provider and customer create value together through their interaction (Ballantyne, 2004; Grönroos & Voima, 2013). Much hinges on combinations of forces. Customers' strategic focus and operation processes as well as regulation and technology, for
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| CONCEPTUAL BACKGROUND
Considering environmental sustainability has become a prerequisite for any business that wants to meet stakeholder expectations and guarantee its operations' long-term success. From a business perspec- tive, the main aim in striving for environmental sustainability is to reduce the negative environmental impacts of corporate activities while strengthening one's economic performance and also factoring in social effects (Khan et al., 2021). Pursuit of sustainability may be moti- vated by demands from regulators, owners, markets, and other stake- holders just as much as the expected economic benefits and the organization's ethics commitments (Baumgartner & Rauter, 2017). Simultaneously, corporate sustainability has become a more strategy- linked issue, involving not only legal compliance but also gaining a competitive edge and managing the business's reputation (Engert et al., 2016). Companies aim to integrate environmental consider- ations into their activities across business-function boundaries, from product design and supply-chain management to business develop- ment and sales (Meuer et al., 2020). In addition, some stakeholders demand that companies take responsibility for sustainable practices throughout the supply chain (Sarkis et al., 2021; Sodhi & Tang, 2019). Increasing availability of data, enabled by digitalization, is chang- ing how businesses operate, thus affecting opportunities to influence environmental sustainability. Data can be defined as objective facts about events and observations of the state of the world (Davenport & Prusak, 1998) or as symbols that represent properties of objects, events, and their environments (Ackoff, 1989). It is only after the transformation of data into knowledge by means of understanding said data in context and elaborating on the valuable patterns uncov- ered that the relevant data can function maximally for environmental sustainability (Ackoff, 1989; Rowley, 2007). Data can add value by driving transparency, optimization, learn- ing, and deeper understanding of such factors as customer needs (Chen et al., 2015). Data's value with specific regard to environmental sustainability lies in the ability to bring environmental considerations into strategic and operative decision-making in an evidence-based manner for business functions such as product design, production planning, supply-chain management, and business models' develop- ment (de Sousa et al., 2019; Langley, 2022). Data afford innovative ways to improve efficiency and, furthermore, monitor and optimize processes and product performances (Niehoff, 2022). This source of information is recognized also for its potential in building transparency among stakeholders (Rusch et al., 2022). The ability of data to aid in setting plausible environmental targets, identifying improvement
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