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Industrial product service systems (IPS²) are required to meet current customer needs in order to provide solutions to current customer problems. Furthermore, adaptability to changing customer decision drivers is required in order to account for customers' preference changes over time. The purpose of this paper is to present an approach where customer preference drivers for different IPS² are identified and their directions analyzed.

A theoretical, literature‐based analysis, drawing on different fields of economic research, is made use of. A tool to anticipate customer decisions based on the identified preference drivers is devised.

Nine main preference drivers are identified. These are customer resources, know‐how, number of employees, core competences, value‐based figures, process intricacy, process standardization, process frequency and process significance.

The drivers identified on a theoretical basis should be investigated empirically. Special consideration should be given not only to the direction of their effect, but also their strength and interdependency.

The paper helps IPS² suppliers to analyze customers' preferences and helps decide about the design and the business model for the IPS².

The paper is the first paper that focuses on the relevant influence factors of a customer's decision about the IPS²‐design.

The majority of existing studies about named entity recognition (NER) concentrate on the prediction enhancement of deep neural network (DNN)-based models themselves, but the issues about the scarcity of training corpus and the difficulty of annotation quality control are not fully solved, especially for Chinese ancient corpora. Therefore, designing a new integrated solution for Chinese historical NER, including automatic entity extraction and man-machine cooperative annotation, is quite valuable for improving the effectiveness of Chinese historical NER and fostering the development of low-resource information extraction.

The research provides a systematic approach for Chinese historical NER with a three-stage framework. In addition to the stage of basic preprocessing, the authors create, retrain and yield a high-performance NER model only using limited labeled resources during the stage of augmented deep active learning (ADAL), which entails three steps—DNN-based NER modeling, hybrid pool-based sampling (HPS) based on the active learning (AL), and NER-oriented data augmentation (DA). ADAL is thought to have the capacity to maintain the performance of DNN as high as possible under the few-shot constraint. Then, to realize machine-aided quality control in crowdsourcing settings, the authors design a stage of globally-optimized automatic label consolidation (GALC). The core of GALC is a newly-designed label consolidation model called simulated annealing-based automatic label aggregation (“SA-ALC”), which incorporates the factors of worker reliability and global label estimation. The model can assure the annotation quality of those data from a crowdsourcing annotation system.

Extensive experiments on two types of Chinese classical historical datasets show that the authors’ solution can effectively reduce the corpus dependency of a DNN-based NER model and alleviate the problem of label quality. Moreover, the results also show the superior performance of the authors’ pipeline approaches (i.e. HPS + DA and SA-ALC) compared to equivalent baselines in each stage.

The study sheds new light on the automatic extraction of Chinese historical entities in an all-technological-process integration. The solution is helpful to effectively reducing the annotation cost and controlling the labeling quality for the NER task. It can be further applied to similar tasks of information extraction and other low-resource fields in theoretical and practical ways.

The march of time is relentless; it brings with it ever increasing technological innovations that cannot bypass or skip over the delivery of personal social services. Within these services, the computer has already found its way to management and research personnel. They itch to put it to use to crunch out the kind of data that they feel they need in order to deliver more cost‐effective services to higher priority targets. The fly in the ointment is the practitioners; they just cannot or will not produce reliable data of the type needed for the number crunchers.

Information technology is a facilitator in knowledge diffusion by enabling individuals to communicate directly in personal exchange. This includes interactive communications through newsgroups and discussion groups. Two discussion groups were analysed, the Social Work Discussion Group SOCWORK, and ABUSE‐L, a professional forum for child abuse issues. Three types of communication were identified: information transfer, requests for information and discussion of issues. The discussion of issues was the main type of communication in both discussion groups, followed by the request for information and then information transfer. Communications in the discussion groups were dominated by a small number of people. Policy issues were the main topic of discussion in both groups. The control of information technology by academics appears to limit the participation of social work practitioners in determining the agenda of the discussion group or the contents of the communications. Social worker practitioners have not increased their access to information even though the technology to make it accessible exists.

Aim of the present monograph is the economic analysis of the role of MNEs regarding globalisation and digital economy and in parallel there is a reference and examination of some legal aspects concerning MNEs, cyberspace and e‐commerce as the means of expression of the digital economy. The whole effort of the author is focused on the examination of various aspects of MNEs and their impact upon globalisation and vice versa and how and if we are moving towards a global digital economy.

Today the amount of all kinds of digital data (e.g. documents and e‐mails), existing on every user's computer, is continuously growing. Users are faced with huge difficulties when it comes to handling the existing data pool and finding specific information, respectively. This paper aims to discover new ways of searching and finding semi‐structured data by integrating semantic metadata.

The proposed architecture allows cross‐border searches spanning various applications and operating system activities (e.g. file access and network traffic) and improves the human working process by offering context‐specific, automatically generated links that are created using ontologies.

The proposed semantic enrichment of automated gathered data is a useful approach to reflect the human way of thinking, which is accomplished by remembering relations rather than keywords or tags. The proposed architecture supports the goals of supporting the human working process by managing and enriching personal data, e.g. by providing a database model which supports the semantic storage idea through a generic and flexible structure or the modular structure and composition of data collectors.

Available programs to manage personal data usually offer searches either via keywords or full text search. Each of these existing search methodologies has its shortcomings and, apart from that, people tend to forget names of specific objects. It is often easier to remember the context of a situation in which, for example, a file was created or a web site was visited. By proposing this architectural approach for handling semi‐structured data, it is possible to offer a sophisticated and more applicable search mechanism regarding the way of human thinking.

This article aims to describe the effects of the communication style of the message sender (threatening or neutral), status of the sender (equal to or higher than the recipient) and the power relationship between sender and recipient (from the same department or not) on the blood pressure of the recipient of an e‐mail message

The study was conducted under controlled laboratory conditions. The experiment was a mixed design, using both within and between subjects variables. The independent variable for the within subjects factor was the task that participants performed. There were three tasks: answering a questionnaire, reading a non‐threateningly worded e‐mail reprimand, and reading a threateningly worded e‐mail reprimand. Although the study used students as participants, the messages they received were from real people in a University College. Discusses the implications in the area of occupational health.

Diastolic blood pressure was significantly higher (p<0.01) when recipients were reading the threateningly worded reprimand compared to reading a non‐threateningly worded reprimand. The effect of status on blood pressure was significant (p<0.05) but only for recipients in the same department as the message sender.

The results add to the evidence that communication style and status can have a direct impact on the recipient's physiological response.