Search results

The purpose of this paper is to investigate the potential of NFTs in revolutionizing innovation management and information systems. Innovations done by firms are blatantly used by other firms to develop cheap knock-off. This leads to huge economic loses to the firm investing in research and development activities. Firms are in need of trusted, immutable and verifiable means of storing information which cannot be used by others, even if publically available without their consent. Non-fungible tokens (NFTs) appear to be one such solution to this problem that has recently attracted a lot of investor interest. Using NFTs the information is tokenized and is stored in a secure manner.

Through this scoping review, the authors investigate the influence of NFTs towards the innovation management from the dual aspects of management and information systems. This scoping review is underpinned by the five-stage framework by Arksey and O’Malley. The five stages of Arksey and O’Malley’s framework were used in this analysis to classify the literature through five stages of identifying the initial research questions; locating relevant studies; study selection; charting the data; and compiling, summarizing and reporting the results.

This study suggests that NFTs on the blockchain have significant potential to revolutionize innovation management and information systems. Theoretical frameworks used in investigating the role of digital tokens in blockchain management are mainly based on contracts, diversity theory, portfolio theory and faking likelihood theory. The study reveals gaps in the literature, particularly in the under-researched areas of behavioural psychology and social psychology theories. The appropriate regulation and regulation authority for different types of digital tokens are required. The study also presents archetypes that represent patterns in the current landscape of blockchain tokens, which have significant potential for future research and practical applications.

This study is unique in its approach to assessing the future of NFTs in the field of innovation and information management. While many existing reviews have focused on describing the progress and development of NFTs in the past, this study takes a forward-looking perspective and projects the future potential of NFTs. This innovative approach allows for a deeper understanding of the potential impact of NFTs in various fields such as entrepreneurship, innovation management and tokenomics. Therefore, this study contributes to the literature on NFTs by providing insights and recommendations for future research and practical applications.

The authors study how enabling perceptions (flexibility, reparability and internal and global transparency) of a budgetary control system are formed, and whether enabling perceptions empower lower-level managers and make them form less negative attitudes about red tape in the organization. This study research is warranted because of the lack of knowledge on how perceptual variation in flexibility, repairability and transparency of a control system within an organization, where managers experiencing the same control system design, can be explained.

Survey data with answers from 211 managers from a large local government organization in Sweden is analyzed with structural equation modeling.

The extent to which the budget system is perceived as having enabling qualities (being flexible, reparable and transparent) is explained by the safeness of the individual manager's psychological climate. This climate is characterized by trust and fairness perceptions in upper management. In turn, enabling perceptions positively affect a sense of psychological empowerment and reduces attitudes toward red tape in the organization.

The authors contribute by identifying an important factor explaining individual-level variability in enabling perceptions of control systems within organizations. Compared to previous research that has taken an interest in the organizational-level climate, the authors theorize about and investigate (parts of) the individual-level psychological climate as an explanation of within-system variability.

On the one hand, there is a long tradition of approaching management control and innovation as opposites that prompt organisational tensions. On the other hand, recent studies have shown that management control may foster innovation and promote innovative behaviour. At the same time, both these perspectives focus on innovation management, and discussions regarding the role of management control in innovation leadership are conspicuously absent from the literature. In this chapter, we analyse how innovation leaders use management control in two service companies. We demonstrate that, in contrast to innovation managers who employ management control systems primarily for planning, monitoring, and evaluation purposes, innovation leaders use management control for advocacy, engagement, and visibility.

This study aims to explore and empirically test variables influencing material delivery schedule inaccuracies?

A mixed-method case approach is applied. Explanatory variables are identified from the literature and explored in a qualitative analysis at an automotive original equipment manufacturer. Using logistic regression and random forest classification models, quantitative data (historical schedule transactions and internal data) enables the testing of the predictive difference of variables under various planning horizons and inaccuracy levels.

The effects on delivery schedule inaccuracies are contingent on a decoupling point, and a variable may have a combined amplifying (complexity generating) and stabilizing (complexity absorbing) moderating effect. Product complexity variables are significant regardless of the time horizon, and the item’s order life cycle is a significant variable with predictive differences that vary. Decoupling management is identified as a mechanism for generating complexity absorption capabilities contributing to delivery schedule accuracy.

The findings provide guidelines for exploring and finding patterns in specific variables to improve material delivery schedule inaccuracies and input into predictive forecasting models.

The findings contribute to explaining material delivery schedule variations, identifying potential root causes and moderators, empirically testing and validating effects and conceptualizing features that cause and moderate inaccuracies in relation to decoupling management and complexity theory literature?

This paper aims to design an AI-based drone that can facilitate the complicated and time-intensive control process for detecting healthy and defective solar panels. Today, the use of solar panels is becoming widespread, and control problems are increasing. Physical control of the solar panels is critical in obtaining electrical power. Controlling solar panel power plants and rooftop panel applications installed in large areas can be difficult and time-consuming. Therefore, this paper designs a system that aims to panel detection.

This paper designed a low-cost AI-based unmanned aerial vehicle to reduce the difficulty of the control process. Convolutional neural network based AI models were developed to classify solar panels as damaged, dusty and normal. Two approaches to the solar panel detection model were adopted: Approach 1 and Approach 2.

The training was conducted with YOLOv5, YOLOv6 and YOLOv8 models in Approach 1. The best F1 score was 81% at 150 epochs with YOLOv5m. In total, 87% and 89% of the best F1 score and mAP values were obtained with the YOLOv5s model at 100 epochs in Approach 2 as a proposed method. The best models at Approaches 1 and 2 were used with a developed AI-based drone in the real-time test application.

The AI-based low-cost solar panel detection drone was developed with an original data set of 1,100 images. A detailed comparative analysis of YOLOv5, YOLOv6 and YOLOv8 models regarding performance metrics was realized. Gaussian, salt-pepper noise addition and wavelet transform noise removal preprocessing techniques were applied to the created data set under the proposed method. The proposed method demonstrated expressive and remarkable performance in panel detection applications.

This paper aims to develop a method based on artificial intelligence capable of predicting the due date (DD) of job shops in real-time, aiming to assist in the decision-making process of industries.

This paper chooses to use the methodological approach Design Science Research (DSR). The DSR aims to build solutions based on technology to solve relevant issues, where its research results from precise methods in the evaluation and construction of the model. The steps of the DSR are identification of the problem and motivation, definition of the solution’s objectives, design and development, demonstration, evaluation of the solution and the communication of results.

Along with this work, it is possible to verify that the proposed method allows greater accuracy in the DD definition forecasts when compared to conventional calculations.

Some limitations of this study can be pointed. It is possible to mention questions related to the tasks to be informed by users, as they could lead to problems in the performance of the artifact as the input data may not be correctly posted due to the misunderstanding of the question by part of the users.

The proposed artifact is a method capable of contributing to the development of the manufacturing industry to improve the forecast of manufacturing dates, assisting in making decisions related to production planning. The use of real production data contributed to creating, demonstrating and evaluating the artifact. This approach was important for developing the method allowing more reliability.

A newly developed frequency-independent lumped parameter model (LPM) is the purpose of the present paper. This new model’s direct outcome ensures high efficiency and a straightforward calculation of foundations’ vertical vibrations. A rigid circular foundation shape resting on a nonhomogeneous half-space subjected to a vertical time-harmonic excitation is considered.

A simple model representing the soil–foundation system consists of a single degree of freedom (SDOF) system incorporating a lumped mass linked to a frequency-independent spring and dashpot. Besides that, an additional fictitious mass is incorporated into the SDOF system. Several numerical methods and mathematical techniques are used to identify each SDOF’s parameter: (1) the vertical component of the static and dynamic foundation impedance function is calculated. This dynamic interaction problem is solved by using a formulation combining the boundary element method and the thin layer method, which allows the simulation of any complex nonhomogeneous half-space configuration. After, one determines the static stiffness’s expression of the circular foundation resting on a nonhomogeneous half-space. (2) The system’s parameters (dashpot coefficient and fictitious mass) are calculated at the resonance frequency; and (3) using a curve fitting technique, the general formulas of the frequency-independent dashpot coefficients and additional fictitious mass are established.

Comparisons with other results from a rigorous formulation were made to verify the developed model’s accuracy; these are exceptional cases of the more general problems that can be addressed (problems like shallow or embedded foundations of arbitrary shape, other vibration modes, etc.).

In this new LPM, the impedance functions will no longer be needed. The engineer only needs a limited number of input parameters (geometrical and mechanical characteristics of the foundation and the soil). Moreover, a simple calculator is required (i.e. we do not need any sophisticated software).

The purpose of this paper is to understand whether and how the Environmental, Social and Governance (ESG) paradigm can be useful in social reporting in the context of nonprofit healthcare organizations. In other words, the study deals with non-financial reporting and information, allowing external stakeholders to comprehensively evaluate the organization’s performance and behavior, investigating internal stakeholder perception over ESG paradigm application.

The authors used a case study approach investigating four cases among nonprofit healthcare organizations in Italy. Analyses of available primary sources have been conducted, followed by semi-structured interviews. Interviews were then transcribed and coded in a joint blinded process by all authors. More specifically, three areas have been investigated: (1) factors motivating the development of non-financial disclosure practices; (2) the rationale behind the organization’s decision to include specific topics; and (3) the future perspective on the future of non-financial disclosure within the specific sector.

ESG may serve as a suitable framework to create comparable documents that can act as benchmarks for similar institutions. However, while nonprofit organizations (NPOs) can draw inspiration from ESG, the utility of these criteria should be thoughtfully tailored to align with the organization’s mission. The ESG using as a general guide, instead of implementing it as a real tool to assess performances, emerges as a positive practice. NPOs should not focus on fulfilling ESG requirements bur rather take inspiration from them. Otherwise, the risk is an excess of focus on the formal aspect rather than on its content.

The study contributes to a better understanding of social and ESG’ reporting activities and approaches in the healthcare sector by describing some case studies and the effect of sustainability in the social reporting of nonprofit healthcare organizations.

As quarterly business reviews (QBRs) remained unexplored in the scholarly community, this paper sheds light on what QBRs are, how they are being used across organisations and provides deep insights into the implementation of the QBR at an incumbent car manufacturer’s digital transformation business unit. Particular attention has been paid to decision processes, portfolio management, challenges and success factors.

Given the explorative nature of the research, a case study is well suited to explore the phenomenon in its real-world context, especially given the dynamic and volatile business environment. This article is based on insights from an incumbent car manufacturer undergoing a business-wide transformation.

The car manufacturer introduced the QBR process and themes to improve business effectiveness and efficiency through (1) focusing on the biggest issues, (2) concentrating efforts, (3) providing autonomy and stability, (4) building and maintaining strong relationships, and (5) building domain expertise. Through the QBR process, themes were (de)prioritised, resources allocated, financial value (estimates) agreed upon, and key performance indicators (e.g. £m/FTE; FTE, full-time equivalent employees) introduced. Digital product managers’ were assigned to the prioritised themes, and portfolio management structures were presented.

Managing short- and long-term objectives is challenging for most businesses but essential to perform well in uncertain environments. The QBR process can help organisations continuously (de)prioritise work and reallocate resources based on changing environments and aligned with strategic priorities.

This study aims to examine the effects of climate change and agricultural technologies on crop production in Vietnam for the period 1990–2018.

Several econometric techniques – such as the augmented Dickey–Fuller, Phillips–Perron, the autoregressive distributed lag (ARDL) bounds test, variance decomposition method (VDM) and impulse response function (IRF) are used for the empirical analysis.

The results of the ARDL bounds test confirm the significant dynamic relationship among the variables under consideration, with a significance level of 1%. The primary findings indicate that the average annual temperature exerts a negative influence on crop yield, both in the short term and in the long term. The utilization of fertilizer has been found to augment crop productivity, whereas the application of pesticides has demonstrated the potential to raise crop production in the short term. Moreover, both the expansion of cultivated land and the utilization of energy resources have played significant roles in enhancing agricultural output across both in the short term and in the long term. Furthermore, the robustness outcomes also validate the statistical importance of the factors examined in the context of Vietnam.

This study provides persuasive evidence for policymakers to emphasize advancements in intensive agriculture as a means to mitigate the impacts of climate change. In the research, the authors use average annual temperature as a surrogate measure for climate change, while using fertilizer and pesticide usage as surrogate indicators for agricultural technologies. Future research can concentrate on the impact of ICT, climate change (specifically pertaining to maximum temperature, minimum temperature and precipitation), and agricultural technological improvements that have an impact on cereal production.

To the best of the authors’ knowledge, this study is the first to examine how climate change and technology effect crop output in Vietnam from 1990 to 2018. Various econometrics tools, such as ARDL modeling, VDM and IRF, are used for estimation.