The 4th International Conference on Modern Management based on Big Data (MMBD2023)

Abstract: The advances in sensing, storage, and networking technology have created huge collections of high-volume, high-dimensional data. Making sense of these data is critical for companies and organizations to make better business decisions, and brings convenience to our daily life. Recent advances in data mining, machine learning, and applied statistics have led to a flurry of data analytic techniques that typically require an iterative refinement process. However, the massive amount of data involved and potentially numerous iterations required make performing data analytics in a timely manner challenging. In this talk, we present a series of data parallel frameworks that accelerate iterative machine learning algorithms for massive data.

Abstract: Blockchains guarantee availability, immutability and transparency of transaction records in distrusted, multi-party application contexts. However, data of interest often originates and is held blockchain-externally and, especially, when such data is confidential, the question arises of how to on-chain data from those external sources without revealing any confidential information. We report on our work on ZoKrates und using zero-knowledge proofs (ZKPs) to realize trustworthy data on-chaining with verifiable off-chain computations: All complex, expensive, and data-intensive computations are executed blockchain-externally, and only select results, commitments, and proofs of off-chain computations are stored on-chain, linked with smart contracts. Doing so, a powerful platform is provided to design and operate innovative business applications. We exemplify this approach for designing energy grids for privacy-enhanced energy exchange, for secure federated learning systems in an IoT health context, and for verifiable carbon accounting in supply chains.

Abstract: Along with the fast-paced development of digital transformation, organisations are using powerful techniques and popular digital platforms to run campaigns to achieve specific communication objectives. Businesses have been developing AI algorithms to enhance the effectiveness and coverage of the communication with audiences. While companies are investing in further advancement of digital communication strategies, there is a real concern on how vulnerable groups are targeted and exposed to the marketing campaigns. For example, children and people with disabilities with less developed cognitive ability as well as socioeconomically disadvantaged people might be adversely affected by digital campaigns. It is time to develop codes of ethics and practices for developing and utilising AI algorithms in order to enforce responsible communication.

Abstract: Enterprise social media (ESM) bring new pathways to enable employees' thriving at work. This study examines the effects of ESM affordances (accessibility, persistence, and association) on employees' thriving at work through structural and psychological empowerment. The research model was examined with data on ESM use gathered from 311 employees. Results show that: a) structural empowerment mediates the effects of ESM accessibility and association on psychological empowerment, b) psychological empowerment mediates the effect of structural empowerment on both dimensions of employees' thriving at work (vitality and learning), and c) accessibility and association positively influence vitality and learning through a chain of mediating effects involving structural and psychological empowerment. The study contributes to the existing ESM literature and suggests that managers should implement appropriate strategies to leverage the value of ESM affordances in empowering employees and enabling them to thrive at work.