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In 2000, Pincott and Branthwaite published 'Nothing New Under the Sun?' which discussed the role of the internet in research both in terms of the hazards and opportunities this confers. Specifically, Pincott and Branthwaite argued that whilst the advent of the internet offers up new approaches and techniques, this must not be at the detriment of methodological rigour and standards we have grown accustomed to in the industry. In this paper, it is argued that the advent of big data, big qual and the emerging potential of the metaverse present new opportunities in research but pose the same questions originally conceived by Pincott & Branthwaite, 2000. Moreover, methodological rigour and standards are framed by three interconnected themes, namely, the role of data science and big data, the importance of softer skills of interpretation and narration and finally, the role of theory in elevating and grounding research. [ABSTRACT FROM AUTHOR]

Artificial intelligence (AI) is an important source of competitive advantage as it enables task augmentation and automation. However, while AI can create significant value, it is important to note that AI investments are fraught with risks and uncertainties. Thus, managers are likely to carefully evaluate potential AI investments before committing to investing. However, we know little about how managers' appraisal of AI influences their investment choices. Drawing upon theorization in the areas of business value of AI, agentic information systems (IS) appraisal, and time-situated agency, we extend existing theory in two ways: (1) development of an AI classification (foundational typology) that proposes two dimensions (action autonomy and learning autonomy) for classifying AI by type and level of autonomy; and (2) development of propositions that leverage time-situated agency and the AI classification to explicate how managers' delegation preferences influence their AI investment appraisal. This paper contributes a foundational theoretical platform for furthering AI investment appraisal research. In addition, the paper sets an agenda for future research in this area. [ABSTRACT FROM AUTHOR]

Purpose: The study explores the extent to which business analytics can address business problems using the task-technology fit theory. Design/methodology/approach: The qualitative research approach of pattern matching was adopted for data analysis and 12 semi-structured interviews were conducted. Four propositions derived from the literature on task-technology fit are compared to emerging core themes from the empirical data. Findings: The study establishes the relationships between various forms of fit, arguing that the iterative application of business analytics improves problem understanding and solutions, and contends that both under-fit and over-fit can be acceptable due to the increasing costs of achieving ideal fit and potential unaffected outcomes, respectively. The study demonstrates that managers should appreciate that there may be a distinction between those who create business analytics solutions and those who apply business analytics solutions to solve problems. Originality/value: Extant studies on business analytics have not focused on how the match between business analytics and tasks affects the level to which problems can be addressed that determines business value. This study enriches the literature on business analytics by linking business analytics and business value through problem resolution demonstrated by task-technology fit. To the authors' knowledge, this study might be the first to apply pattern matching to study the fit between technology and tasks. [ABSTRACT FROM AUTHOR]

The relevance of the research is justified by the need to search for new factors of business value formation, which are taken into account by stakeholders when making decisions. The purpose of the article is to analyze the influence of S- and G- factors on the value formation of Russian public companies in the manufacturing sector and to substantiate the importance of disclosing the indicators of sustainable development of companies as a factor of business growth. The study uses methods and tools of correlation, causal and comparative analysis. It was found that the position occupied in the RAEX ranking by S- and G- factors and the amount of capitalization are significantly correlated for companies in the extractive and manufacturing industries. There was found no statistically significant relationship between the considered indicators in relation to the companies of the agro-industrial complex. It is confirmed that the influence of sustainable development components on the formation of the companies’ value is different depending on their industry affiliation. The necessity to take into account ESG factors in the methods of comparative and income approaches is substantiated. The directions of ESG factors accounting in the methods of comparative and income approaches are highlighted. The scientific novelty of the research is determined by the substantiation of the necessity of separate accounting of the sustainable development components in the formation and assessment of business value. The practical significance of the study is that the results obtained by the author can be used by investors, owners and practicing appraisers in making managerial decisions and assessing and determining business value.

In the present digital environment, a data-driven organizational culture has become a vital emerging driver of organizational growth. This data-driven culture has assumed an advanced shape due to adoption of artificial intelligence (AI) integrated business analytics tools in the organization. Data-driven culture in the organization could considerably impact product innovation strategy as well as organizational process alteration. In this context, the aim of this study is to investigate how an organization's data-driven culture impacts process performance and product innovation that led to enhanced organizational overall performance and higher business value. Methodologically, supported by relevant extant literature and inputs from the resource-based view and dynamic capability theories (organizational context), a conceptual model and a set of hypotheses are initially developed. These are subsequently statistically validated through a survey involving 513 usable responses from employees of different organizations using business analytics tools embedded with AI capability. The findings demonstrate that an organizational data-driven culture has considerable moderating impact on product innovation and process improvement, which ultimately enhance business value through improved organizational overall performance. [ABSTRACT FROM AUTHOR]

This paper explores the factors that facilitate and impede blockchain technology adoption (BTA) within business organizations. Analysing 112 scholarly articles via thematic and bibliometric methods reveals a complex adoption landscape, highlighted by the proposition of an innovative conceptual framework that augments the conventional technology-organization-environment (TOE) framework. This augmented framework integrates enabling factors, such as enhanced security mechanisms via smart contracts, and barriers, including scalability challenges and regulatory limitations. The research offers significant insights into cultivating a conducive ecosystem for BTA within organizations and provides practical implications. [ABSTRACT FROM AUTHOR]

The article suggests a Value Proposition (VP) framework that enables analysis of the beneficial impact of Artificial Intelligence (AI) resources and capabilities on specific VP activities. To develop such a framework, we examined existing business and management research publications to identify and extract assertions that could be used as a source of actionable insights for early-stage growth-oriented companies. The extracted assertions were assembled into a corpus of texts that was subjected to topic modelling analysis—a machine learning approach to natural language processing that is used to identify latent themes in large corpora of text documents. The topic modelling resulted in the identification of seven topics. Each topic is defined by a set of most frequent words co-occurring in a distinctive subset of texts that could be interpreted in terms of activities constituting the core elements of the VP framework. We then examined each activity in terms of its potential to be enhanced by employing AI resources and capabilities. The interpretation of the topic modelling results led to the identification of seven topics: (1) Value created; (2) Stakeholder value propositions; (3) Foreign market entry; (4) Customer base; (5) Continuous improvement; (6) Cross-border operations; and (7) Company image. The uniqueness of the adopted topic modelling approach consists in the quality of the assertions and the interpretation of the seven topics as an activity framework, i.e., in its capacity to generate actionable insights for practitioners. The additional analysis suggests that there is a potential for AI to enhance the emerging four core elements of the VP framework: Value created, Stakeholder value propositions, Foreign market entry, and Customer base. More importantly, we found that the greatest number of assertions related to activities that could be enhanced by AI are part of the Customer base topic, i.e., the topic that is most directly related to the growth potential of the companies. In addition, the VP framework suggests that a company's customer base growth is continuously enhanced through a positive loop enabled by activities focused on the Continuous improvement of the activities and the amount of Value created, the alignment of Stakeholder value propositions, and companies' Foreign market entry. Thus, the multiple-stakeholder perspective on VP development and foreign market entry appears as a factor that helps in understanding the beneficial impact of AI on the enhancement of the VP of early-stage growth-oriented companies. [ABSTRACT FROM AUTHOR]

A reliable assessment of the value of a business and its ability to create, preserve, and lose value depends on identifying the factors that affect it. The factors are determined taking into account the interests of financial capital providers and the ability to increase the investment attractiveness of the enterprise. The relevance of the study is due to the need to identify key factors in the context of integrated reporting. That is, there is a need to determine what key factors are of interest to financial capital providers, have an impact on the cost of capital and the total value of the enterprise. The aim of the article is to analyze approaches in scientific publications to the classification of business value creation factors as a basis for their identification and monitoring. The following methods were used in the course of the study: analysis and synthesis; comparison; systematization; deduction. During the study, approaches to the classification of value creation factors used by domestic and foreign scientists were analyzed, as well as approaches to classification, which are provided by the International Framework for Integrated Reporting. It is found that the vast majority of scholars distinguish the factors of both the internal and external environment. Upon closer examination, it is found that there are differences in their understanding. In addition, it is found that the International Framework for Integrated Reporting focuses on external factors that are not controlled by the enterprise. As a result of the study, a system of approaches to the classification of factors of business value creation has been developed using such features as: place of occurrence of the factor; method of impact; the ability to control (manage) the impact; the time of manifestation of the factor; duration of impact; degree of dependence on other factors; consequences (nature) of the impact and materiality of the impact. In practice, the application of the proposed system of classification of business value creation factors in any case will help to identify and define the key factors that have a significant impact on the cost of capital and the value of the enterprise as a whole. In addition, it will allow the enterprise to assess the likelihood of a risk of reduction and the possibility of increasing the value of the business, the scale of such changes; identify the specific circumstances that may lead to the materialization of the risk or the exploitation of the opportunity; take appropriate measures and develop targets to monitor the impact of key factors on business value.

The study focuses on a detailed analysis and evaluation of the key elements that foster the development of more effective and adaptive business strategies. The study found that the process of creating business strategies reflects a variety of approaches, ranging from traditional methods to modern innovative solutions. The main approaches are divided into: business value creation, targeted planning and integrated measures. It is revealed that modern business strategies are evolving, taking into account a wide range of important aspects, including environmental and social benchmarks of sustainable development. It is also noted that the development of information technology contributes to approaches to business strategies, forcing companies to be more flexible and quickly adapt to changes. It is found that the development and selection of business strategies are fundamental to the success of each company, requiring a thorough analysis of external and internal factors that affect its opportunities and risks. It is noted that the external environment affects the availability of resources and determines the competitive position of an enterprise, while the internal environment determines the internal capabilities and potential of an organization to implement strategic plans. It is emphasized that the effectiveness of a strategy is ensured by continuous collection of information about the external and internal environment, evaluation of results and making adjustments to the strategy in accordance with changes in the external and internal environment of the enterprise. It is emphasized that understanding the needs and expectations of stakeholders, such as customers, employees, suppliers, shareholders, government and the local community, is key to creating effective strategies that contribute to the achievement of the company's goals. It is indicated that the choice of a particular strategy largely depends on stakeholders and resources. It is also emphasized that in the context of strategic planning, the resources of enterprises need to be transformed, in particular, staff – into intellectual capital, current assets – into innovations, capital investments – into sustainable development technologies, and information – into interaction. The practical significance of the topic is to improve the process of forming effective business strategies, which contributes to the competitive advantage and sustainable development of the company.

The complexity of industrial challenges is emerging together with the exponentially developing information and communication technologies (ICT) that provide several implementation approaches for systems engineering. It is difficult for a single company to follow technological development and remain a pioneer in every topic. Still, the industrial challenges require experts in each technology. Therefore, collaboration among technology providers is an opportunity to gather all resources and competences needed for full delivery. A joint offering (JO) is a solution, that is, co‐created in collaboration between two or more actors that usually have complementary technological skills or value‐creation logics. A JO has several doubts relating to the use case (UC) in hand, the feasibility of the joint solution to be co‐created, the resources and skills needed to deliver the joint solution, the partners, the business value creation, the elements of the contract and the ownership of the outcome, just to mention a few. The Joint Offering Evaluation Framework (JOEF) uncovers these issues and supports decision‐making before the development of a JO starts. The JOEF comprises the Joint Offering Playbook and the Business Value Toolset (BVT). The Playbook offers seven viewpoints with checklists and tools for IT solution providers considering collaboration and co‐creation for a solution that they cannot deliver or sell alone. The BVT evaluates and illustrates the business value of a JO from the viewpoints of both creation and delivery, together with value capture and assessment. The JOEF was piloted with a digital twin (DT) UC from the pulp and paper industry. [ABSTRACT FROM AUTHOR]

Purpose: To achieve digital transformation, organizations have continued to rely on integrating the capabilities of information technology (IT) to facilitate decision-making and developing their reconfiguration capability to enhance agile operations. The pressure imposed by digital transformation necessitates investigations on leveraging different IT capabilities to attain substantial organizational agility in an optimal configuration. This study aims to provide a new perspective on balancing IT structural capabilities and proposes a framework for evaluating their coalignment and complementary returns based on resource orchestration theory. Design/methodology/approach: A multi-method approach is used to evaluate the research model. This study tests hypotheses and explores the potential coalignment and complementary returns of balance in structural models and response surface analysis. Then, it analyzes the qualitative data and provides complementary findings to corroborate and confirm complex relationships. Findings: Balanced structural IT capabilities facilitate organizational agility but cooperate differently with internal (e.g. IT proactive stance) and external (e.g. environmental volatility) environmental factors. Balance between IT integration and reconfiguration must be maintained from several approaches during search/selection and configuration/deployment. Originality/value: This study theorizes and empirically investigates the interactive mechanisms of two IT capabilities in influencing organizational agility under different boundary conditions. It enriches the understanding of balancing capabilities for organizational agility in digital transformation. [ABSTRACT FROM AUTHOR]

Metaverses refer to immersive virtual worlds in which people, places, and things of the physical world are represented by their digital representations. The wide adoption of metaverses is expected to widely disrupt the way we interact in the virtual world by elevating our online interactive experiences and bringing a plethora of implications for businesses. Following a structured literature review of related research published in the last decade, we shed light on our current understanding of metaverses and reflect on the potentially transformative value of metaverses for businesses in the near future. We draw on an established research framework to organize the insights of existing literature across different levels of analysis and activities' purpose. Through this analysis, we reveal eight propositions on the changes brought by the use of metaverses and identify a number of open questions which could serve as future research avenues. [ABSTRACT FROM AUTHOR]

Background/ Objectives: Big Data is a tremendously large data set that has been analyzed, managed, managed and validated through a regular info management application. Banks are of all financial services industries, that handle overwhelming quantities of transaction info managed, scrutinized, in addition to employed for the gain of banks and definitely the customers. Thus, this specific analysis paper examined how BDA is handled in Malay/Indian/Indonesian manufacturing banks. The elements which have a larger impact on banks in handling large data were analyzed, in addition to how analytics generates worth for the business. Method/Statistical Analysis: Secondary data was collected from several sources, such as articles, journals and websites. The elements including great data management, consumer segmentation, risk management, fraud detection, in addition to business value of banking industries are studied. A conceptual framework was produced to spotlight the components that have a much better impact on big data management in the banking business. Findings: From the analysis, it's examined that big data analytics has pushed a noticeable change in the business worth of banks, as well as the components that influence the organization. Application/Improvements: Banks must revamp their software architecture for dealing with key information, and stick to the brand new technologies which boost the internet business worth of the company.

Social media has become a component of living for more people worldwide. Businesses are undoubtedly using it to instantly and easily create, in addition to share information with all the customers and gain gained from this seamless interaction. Due to the improved social media platforms and members, the wish to watch, extract, analyze and report the info created on these platforms has also enhanced many businesses. Current labor identifies the social media analytics progression and internet show application. It identifies the different phases of the SMA process, together with their integration on the internet, to show strategy, options, and difficulties. SMA metrics for the client life cycle are discussed. A comparative analysis is still presented for different SMA plans to identify their energy to the web FMCG.

This paper presents an extended approach to Impact Assessment (IA) within European Union funded large-scale projects within the manufacturing domain, which may offer value to other research projects and SME organisations seeking to develop detailed organizational reporting. It details the six-phase process that forms the framework for this extended approach, demonstrating how project Outcome Indictors and impact assessment criterion can be aligned through an extensive review and integration of existing impact domains, objectives, measures and evidence sources with project documentation to provide the detailed individual impact assessment criteria for this extended IA approach. It also reports on the application of the approach in the EC-funded digital manufacturing project, European Connected Factory Platform for Agile Manufacturing (EFPF), finding that 24 of the 27 IA criteria were met or exceed, suggesting that the project made an important contribution to the EU Industry4.0 ecosystem through furthering the key priorities of Industrial Leadership, Data Integration, Uptake of New Technologies, Open Science, the Circulation of Knowledge, and a minor contribution to Climate Change Mitigation.

Explainable Artificial Intelligence (XAI) has gained significant attention as a means to address the transparency and interpretability challenges posed by black box AI models. In the context of the manufacturing industry, where complex problems and decision-making processes are widespread, the XMANAI platform emerges as a solution to enable transparent and trustworthy collaboration between humans and machines. By leveraging advancements in XAI and catering the prompt collaboration between data scientists and domain experts, the platform enables the construction of interpretable AI models that offer high transparency without compromising performance. This paper introduces the approach to building the XMANAI platform and highlights its potential to resolve the “transparency paradox” of AI. The platform not only addresses technical challenges related to transparency but also caters to the specific needs of the manufacturing industry, including lifecycle management, security, and trusted sharing of AI assets. The paper provides an overview of the XMANAI platform main functionalities, addressing the challenges faced during the development and presenting the evaluation framework to measure the performance of the delivered XAI solutions. It also demonstrates the benefits of the XMANAI approach in achieving transparency in manufacturing decision-making, fostering trust and collaboration between humans and machines, improving operational efficiency, and optimizing business value.

This paper expands a methodology, originally formulated for calculating the firm-level business value of Information Technology (IT), to that for a whole sector and applies it experimentally for the transport sector using statistical databases for several countries in Europe. The term “business value” means the quantified impact of a given technology, in this case, Information Technology, on the productivity of a sector or firm as measured by a given “yardstick” (e.g., sales, revenue, and many others). This is important to know in order to justify investments in a given technology or technological sector and for policy formulation or regulation. This paper proposes a novel methodology for calculating the business value of IT in a given sector. This is the first time that such a task is attempted because in the past most research was focused on calculating the business value at firm-level. The suggested methodology is then applied by use of panel data from the statistical records of national statistics for the transport sector. The results show that infrastructural investment in Information Technology has an impact on the transport sector’s output, in terms of its annual production value, of the order of 5–6%. Through sensitivity tests and a discussion of the results, it is estimated that the actual impact may probably be a bit higher but not much higher (in any case, something below the 10% figure). The application also shows that the suggested methodology can be applied for the estimation of the impact of any other technology or service on any given economic sector. Finally, a possible future conceptual model is presented for the expansion of the methodology to a more global and integrated level considering the interaction from other sectors as well as other technological and environmental factors.

The article suggests a Value Proposition (VP) framework that enables analysis of the beneficial impact of Artificial Intelligence (AI) resources and capabilities on specific VP activities. To develop such a framework, we examined existing business and management research publications to identify and extract assertions that could be used as a source of actionable insights for early-stage growth-oriented companies. The extracted assertions were assembled into a corpus of texts that was subjected to topic modelling analysis—a machine learning approach to natural language processing that is used to identify latent themes in large corpora of text documents. The topic modelling resulted in the identification of seven topics. Each topic is defined by a set of most frequent words co-occurring in a distinctive subset of texts that could be interpreted in terms of activities constituting the core elements of the VP framework. We then examined each activity in terms of its potential to be enhanced by employing AI resources and capabilities. The interpretation of the topic modelling results led to the identification of seven topics: (1) Value created; (2) Stakeholder value propositions; (3) Foreign market entry; (4) Customer base; (5) Continuous improvement; (6) Cross-border operations; and (7) Company image. The uniqueness of the adopted topic modelling approach consists in the quality of the assertions and the interpretation of the seven topics as an activity framework, i.e., in its capacity to generate actionable insights for practitioners. The additional analysis suggests that there is a potential for AI to enhance the emerging four core elements of the VP framework: Value created, Stakeholder value propositions, Foreign market entry, and Customer base. More importantly, we found that the greatest number of assertions related to activities that could be enhanced by AI are part of the Customer base topic, i.e., the topic that is most directly related to the growth potential of the companies. In addition, the VP framework suggests that a company’s customer base growth is continuously enhanced through a positive loop enabled by activities focused on the Continuous improvement of the activities and the amount of Value created, the alignment of Stakeholder value propositions, and companies’ Foreign market entry. Thus, the multiple-stakeholder perspective on VP development and foreign market entry appears as a factor that helps in understanding the beneficial impact of AI on the enhancement of the VP of early-stage growth-oriented companies.

Artificial Intelligence and Analytics (AI&A) are used in various application areas ranging from online entertainment to healthcare. The goal of this Special Issue is to focus on how AI&A are used in practice to assist organisations to create economic value, support decision making, transforming them, and enhance employees' skills such as communication, innovation, and decision-making. To derive actionable insights on the application of AI&A in practice, the five articles selected for this Special Issue feature both rigorous academic research and reflections and actionable lessons for professionals. This editorial contains a brief overview of the articles included in this special issue. [ABSTRACT FROM AUTHOR]

The purpose of the article is the analysis of capital valuation methods in the integrated reporting of enterprises and the formation of an appropriate system of indicators for determining the value of the business. A condition for displaying capital in integrated reporting is their assessment, i.e. characterization using a system of relevant indicators. The analysis of scientific publications and integrated reports of enterprises showed that there are different approaches to the assessment of each type of capital. For this, both financial (monetary and non-monetary) and non-financial indicators are used. Quantitative indicators are very important for explaining the practice of the organization's use of various capitals and their changes. Qualitative indicators help to better disclose information for capital evaluation. There is no formalized or generally recognized list of indicators for characterizing enterprise capital. Therefore, enterprises must independently determine them, based on the type of their economic activity. Likewise, there is no unanimity regarding the methods of capital assessment for their reflection in integrated reporting. Their choice depends on the selected indicator system. The proposed division of indicators into general and additional allows for a more systematic approach to the development of their system by types of capital. In addition, it is advisable to take into account that certain indicators can be used to characterize two or more capitals. The obtained results open up new areas of further research that will help answer questions about the formation of the total value of business, in particular: definition and systematization of a list of universal indicators of capital assessment in integrated reporting (general), which can be used at enterprises regardless of their type of activity (or/and which are most relevant for providers of financial capital); a more detailed analysis of how the value of each of the capitals at enterprises is formed and their impact on the overall value of the business; determination of capital valuation methods and approaches that can be used to reliably determine business value. [ABSTRACT FROM AUTHOR]

This paper expands a methodology, originally formulated for calculating the firm-level business value of Information Technology (IT), to that for a whole sector and applies it experimentally for the transport sector using statistical databases for several countries in Europe. The term "business value" means the quantified impact of a given technology, in this case, Information Technology, on the productivity of a sector or firm as measured by a given "yardstick" (e.g., sales, revenue, and many others). This is important to know in order to justify investments in a given technology or technological sector and for policy formulation or regulation. This paper proposes a novel methodology for calculating the business value of IT in a given sector. This is the first time that such a task is attempted because in the past most research was focused on calculating the business value at firm-level. The suggested methodology is then applied by use of panel data from the statistical records of national statistics for the transport sector. The results show that infrastructural investment in Information Technology has an impact on the transport sector's output, in terms of its annual production value, of the order of 5–6%. Through sensitivity tests and a discussion of the results, it is estimated that the actual impact may probably be a bit higher but not much higher (in any case, something below the 10% figure). The application also shows that the suggested methodology can be applied for the estimation of the impact of any other technology or service on any given economic sector. Finally, a possible future conceptual model is presented for the expansion of the methodology to a more global and integrated level considering the interaction from other sectors as well as other technological and environmental factors. [ABSTRACT FROM AUTHOR]

This paper investigates enterprise resource planning (ERP) implementations to improve the ability to realize outstanding value from such systems. In particular, it aims to provide a deep understanding of realizing sustainable value from ERP systems and to examine the relevance of benefits management (BM) in this context. To do so, this research applied a qualitative case study approach to investigate the implementation of Tier-1 ERP systems in two firms. Key findings initially suggest five considerations to better understand the realization of benefits from ERP implementation. Consequently, this research outlines the key activities undertaken by the investigated organizations and aligns them with activities suggested by benefits management literature. In conclusion, this research conjectures that while benefits management is a good practice and a systematic approach to realizing benefits from information systems, it may be ineffective in addressing the benefits that emerge in practice, i.e., when integrating the ERP system with modern digital technologies. Therefore, this research advocates either revisiting the current BM techniques or improving the implementation of digital technologies, including ERP systems with BM concepts and principles by incorporating such BM concepts within the implementation process. This study responds to research calls for maximizing the returned value from the implemented ERP systems by providing insightful recommendations. [ABSTRACT FROM AUTHOR]

Business Analytics is one of the vital processes that must be incorporated into any business. It supports decision-makers in analyzing and predicting future trends based on facts (Data-driven decisions), especially when dealing with a massive amount of business data. Decision Trees are essential for business analytics to predict business opportunities and future trends that can retain corporations' competitive advantage and survival and improve their business value. This research proposes a tree-based predictive model for business analytics. The model is developed based on ranking business features and gradient-boosted trees. For validation purposes, the model is tested on a real-world dataset of Universal Bank to predict personal loan acceptance. It is validated based on Accuracy, Precision, Recall, and F-score. The experiment findings show that the proposed model can predict personal loan acceptance efficiently and effectively with better accuracy than the traditional tree-based models. The model can also deal with a massive amount of business data and support corporations' decision-making process. [ABSTRACT FROM AUTHOR]

This paper aims to develop a comprehensive procedure for calculating the fair value of a company by predicting its future values using historical data of key ratios and applying dynamic algorithms to improve the selection of forecasting methods. The most important business valuation methodologies are based on discounting a firm's future variables, and there are many ways to predict them through financial and quantitative methodologies. This paper provides the most important and commonly used time series forecasting methodologies that can be used for variables, such as financial ratios, and proposes three different algorithms to help and improve the selection of the best-fit method for each of the model's variables. Another, more indirect way of predicting values is using operational research methodologies, such as Monte Carlo simulation, where the output of the sensitivity analysis gives the most likely firm value, taking into account the distribution of each variable. This paper includes a complete example of using the above procedures in a real Greek company to calculate its fair value. It offers alternative approaches to the problem that exists around the process of predicting variables, with the help of technology. We hope this will be a useful tool for future use. [ABSTRACT FROM AUTHOR]

Social customer relationship management (CRM) is software that can integrate different social media channels. Using social CRM, employees can leverage social information of existing and potential customers; gain detailed market insights from their likes and dislikes; provide superior customer services; help to communicate product information more efficiently and effectively to targeted customers. The present article, thus, examines the role of social CRM capability in online marketing communication. Towards this aim, the study has developed a theoretical model based on explicit knowledge derived from the literature, as well as from the dynamic capability view (DCV) and absorptive capacity theories. The model has been validated and the hypotheses have been tested with the factor-based partial least squares (PLS) structural equation modeling (SEM) technique that analyzed the quantified responses of 310 employees of Indian firms. This research is unique and substantially contributes to extant theory and practice, as it is the only one to have extensively analyzed the role of social CRM ability in the context of online marketing communication; demonstrating, conclusively, a significant positive impact of social CRM on online marketing communication. [ABSTRACT FROM AUTHOR]

In software systems, user experience (UX) is a quality that provides value to its intended users. Therefore, we consider it critical to manage UX and its link to business value quantitatively. Key performance indicators (KPIs) have been widely adopted for objectively measuring factors that influence business success, including measuring UX characteristics and their business contribution in the context of software systems in general. Yet, measuring UX in the context of complex Internet of Things (IoT) systems, especially Industrial IoT (IIoT) systems, remains a challenge.This paper presents a multivocal literature review (MLR) of the UX-KPIs proposed in the context of (I)IoT systems, along with factors influencing UX and challenges of quantifying UX. We investigate the status quo and derive recommendations for measuring the UX of (I)IoT systems.Our analysis of 64 publications shows that UX has so far received relatively little attention in the context of (I)IoT. Although we identified 605 KPIs, 78 influencing factors, and 119 challenges, most of the UX features discussed were defined in a broader context of software systems, i.e., they were less specific to IoT, but rather focused on universal system quality characteristics such as functional suitability, performance efficiency, usability, and reliability.Finally, no generally accepted approach for measuring UX in (I)IoT systems and how these contribute to the overall business value has been proposed yet. We also found little evidence that improving UX or achieving a good UX currently plays an explicit role in the design and development of IoT systems.

For organizations, the development of new business models and competitive advantages through the integration of artificial intelligence (AI) in business and IT strategies holds considerable promise. The majority of businesses are finding it difficult to take advantage of the opportunities for value creation while other pioneers are successfully utilizing AI. On the basis of the research methodology of Webster and Watson (2020), 139 peer-reviewed articles were discussed. According to the literature, the performance advantages, success criteria, and difficulties of adopting AI have been emphasized in prior research. The results of this review revealed the open issues and topics that call for further research/examination in order to develop AI capabilities and integrate them into business/IT strategies in order to enhance various business value streams. Organizations will only succeed in the digital transformation alignment of the present era by precisely adopting and implementing these new, cutting-edge technologies. Despite the revolutionary potential advantages that AI capabilities may promote, the resource orchestration, along with governance in this dynamic environment, is still complex enough and in the early stages of research regarding the strategic implementation of AI in organizations, which is the issue this review aims to address and, as a result, assist present and future organizations effectively enhance various business value outcomes. [ABSTRACT FROM AUTHOR]

Purpose: The goal of this article is to provide a tutorial for measuring the sustainability impacts of our content. Sustainability considerations should be just as important as the accessibility and usability of content. Fortunately, following our known best practices for effective content creation and governance also results in a smaller carbon footprint. This not only benefits the planet but also positions content creators as valuable business assets. Method: An extensive literature review led to the development of processes and guidelines that connect our existing best practices for content with a new paradigm for sustainable content. Results: This tutorial will examine five content scenarios and the relative impacts of each: modifications to individual web pages, content governance (removal of redundant, outdated, and trivial content), email blasts, videos, and podcasts. Metrics will be provided for justifying content decisions to management, and recommendations will be given for both optimizing usability and sustainability. Conclusion: Merging established best practices for content creation and curation with measurable energy-to-emissions data gives us powerful tools for justifying content choices and demonstrating measurable value to both the organization and the planet. [ABSTRACT FROM AUTHOR]

Neuromarketing is a branch in the field of commercial marketing communication. Neuromarketing closely relates to neuropsychology and market research for studying the cognitive thinking process of customers and their responses to the marketing stimuli. Presently no study has investigated the moderating role of firm leadership support in promoting neuromarketing applications in their firm. However, there is a huge interest among researchers and industry practitioners to understand this phenomenon and how leadership support can sponsor and invest in neuromarketing related programs in their marketing departments. Against this background, the objective of this study is to examine the role of firm leadership support in promoting neuromarketing and the consequences of it. With the help of marketing theories and literature, a theoretical model has been developed. Later, the model is validated using the CB-SEM technique using 372 responses from employees in marketing departments of various firms. The study finds that there is a significant and positive impact of neuromarketing on customer loyalty, improving business value, and marketing performance of the firms, which in turn significantly impacts the competitive advantage of the firms. The study also finds that leadership support plays an important role in promoting neuromarketing related applications in the firms. [ABSTRACT FROM AUTHOR]