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This study aims to synthesize and analyze research on the Supply Chain Management Practices (SCMPs)-performance nexus, examine current knowledge, identify emerging trends, and provide plausible suggestions for future research engagements in the manufacturing sector in the context of Developing and Emerging Economies (DEEs).

Following a systematic review approach, this study analyzed 20 peer-reviewed scientific journal articles published between 2007 and 2021. The study sample was systematically selected from the Web of Science (WoS) and Google Scholar databases, following strict evaluation and selection criteria.

Numerous dimensions of SCMPs have been considered in the extant literature; however, six have stood out as the most common. In addition, operational performance stood out as the most widely investigated measure in the SCM literature. Moreover, SCMPs have predominantly shown positive effects on performance outcomes. Methodological issues that future studies should consider are suggested.

The sample size was not sufficiently large relative to the rule of thumb set in the literature because of the scarcity of studies in the manufacturing sector in the DEEs context. Despite these limitations, the results of this study provide crucial insights into knowledge and practice.

This review is the first of its kind to examine the SCMPs-performance nexus in the context of DEEs. Based on the findings of this study, future research directions are proposed.

The purpose of this paper is to describe UWIRS (Ubiquitous Web Information Retrieval Solution), an agent‐based Web Information Retrieval (WIR) solution designed taking into account the unique features of the World Wide Web (WWW) and the limitations of existing WIR solutions for ubiquitous environments.

UWIRS can offer recommendation services by using the Multi‐Agent Vizier Recommendation Framework (Vizier). Vizier was designed under a generic approach and therefore can provide services to information retrieval applications so these may offer product recommendations that consider several adaptation/personalization dimensions (e.g. user dimension, context, among others).

Overall, the main challenge resides on: location, retrieval, integration and presentation of information from the WWW, quickly and accurately, to satisfy a user's singular information needs.

In UWIRS, agents cooperate in order to retrieve personalized information, considering user needs, goals, preferences and contextual features. UWIRS's agents are responsible for: interpreting user input and adding adaptation information by means of a query enrichment process; identifying and selecting the appropriate data sources taking into consideration the Profile Set (composed of User, Device and Information‐Provider Profiles); executing query routing and the information retrieval process; integrating and filtering the retrieved results; and lastly, coherent presentation of quality and relevant ubiquitous information (anytime, anywhere and anyhow) that satisfies the user's particular information needs and constraints associated to his/her access device.

Nobody concerned with political economy can neglect the history of economic doctrines. Structural changes in the economy and society influence economic thinking and, conversely, innovative thought structures and attitudes have almost always forced economic institutions and modes of behaviour to adjust. We learn from the history of economic doctrines how a particular theory emerged and whether, and in which environment, it could take root. We can see how a school evolves out of a common methodological perception and similar techniques of analysis, and how it has to establish itself. The interaction between unresolved problems on the one hand, and the search for better solutions or explanations on the other, leads to a change in paradigma and to the formation of new lines of reasoning. As long as the real world is subject to progress and change scientific search for explanation must out of necessity continue.

Nonperforming assets in any banking system have stressed the economic health of nations. Resultantly, literature has given considerable impetus to predict failures and bankruptcy. Past studies have focused on the outcome of failures, while, there is a dearth of studies focusing on ongoing firms in bad shape. We plug this gap and attempt to identify underlying communication patterns for firms witnessing prolonged underperformance. Using text mining, we extract and analyze semantic, linguistic, emotional, and sentiment-based features in non-numeric communication channels of these poor-performing firms and their peers. These uncovered patterns highlight the use of vocabulary and tone of communication, in correspondence to their financial well-being. Furthermore, using such patterns, we deploy various Machine Learning algorithms to identify loser firm(s) way ahead in time. We observe promising accuracy over a time window of five years. Such early warning signals can be of critical importance to various stakeholders of a firm. Exploration of writing style-related features for any firm would help its investors, lending agencies to assess the likelihood of future underperformance. Firm management can use them to take suitable precautionary measures and preempt the future possibility of distress. While investors and lenders can be benefitted from this incremental information to identify the likelihood of future failures.

Relative to comparable industrialized countries, Germany stands out in terms of its low homeownership rate (43 percent). For Germany, it is unknown so far to what extent the low rate of homeownership can be related to housing being unaffordable. One reason for the lack of evidence is the apparent lack of data. The purpose of this paper is to fill this gap.

Based on a regional dataset of 3.9 million asking prices of housing units collected by a real estate listing engine, the paper applies internationally established affordability concepts to the German housing market. The authors then run a number of cross‐section regressions at the level of the 16 German federal states, using the affordability measures as explanatory variables of the rate of homeownership.

The results show that the average German household would have to sacrifice a large part of its non‐housing consumption to afford homeownership, especially of single‐family homes. As the regional analysis reveals, certain types of household can even be considered excluded from the ownership market in some particularly unaffordable states with cost burdens of over 50 percent, such as Bavaria. The cross‐section regression results for the 16 federal states affirm the importance of affordability as a determinant of the homeownership rate.

The official data on ownership rates are rather spotty over time and only available for a single year (2006) for the time frame that is considered for the affordability analysis (2005‐2010). Given the data limitations, the regression analysis has to be confined to a single cross section least squares regression for 2006. The authors are aware that to obtain truly convincing results, it would be necessary to capture the development of ownership rates in different localities in Germany, such as the 16 federal states, over time and to check to what extent the affordability measures can explain any of the variation in ownership rates in a panel data framework with fixed effects for federal states and time. However, the authors feel that the regression results may serve as a starting point; they are better than a set of simple correlations, even if they constitute not a conclusive causal analysis.

Any public policy initiative to raise Germany's homeownership rate will have to address the question of how to make housing more affordable. The recent elimination of homeowner subsidies is working in exactly the opposite direction.

The affordability approach used is technically not new or challenging, but it offers a basis for comparison that has been conspicuously lacking so far for the fourth largest economy of the world. By applying affordability concepts that are well accepted and in use internationally, the authors believe that they can provide at least some suggestive evidence that can further spur research into the affordability issue. While the authors do not break new methodological ground with their paper, they do provide a basis of comparison for policy discussion and for further research. Germany provides a unique environment for affordability research, due to its reunification history, observations from which may thus yield insights valuable to the international research community.

THE Reference Department of Paisley Central Library today occupies the room which was the original Public Library built in 1870 and opened to the public in April 1871. Since that date two extensions to the building have taken place. The first, in 1882, provided a separate room for both Reference and Lending libraries; the second, opened in 1938, provided a new Children's Department. Together with the original cost of the building, these extensions were entirely financed by Sir Peter Coats, James Coats of Auchendrane and Daniel Coats respectively. The people of Paisley indeed owe much to this one family, whose generosity was great. They not only provided the capital required but continued to donate many useful and often extremely valuable works of reference over the many years that followed. In 1975 Paisley Library was incorporated in the new Renfrew District library service.

The purpose of this paper is to provide appropriate methods for reducing the abnormalities on the extracted fetal heart signal from the maternal electrocardiogram (ECG).

In this regard, the extracted signal of the fetal heart from the mother, improved using an active noise cancelation (ANC) system. It uses commonly adaptive algorithms of normalized least mean squares (NLMS). In the present paper, fetal extraction and denoising methodology are proposed. This methodology uses a combination of the NLMS algorithm with Savitzky–Golay (S-G) filter.

The obtained results show that a combination of NLMS algorithm with filter coefficient of 15 and µ = 0.02 and S-G filter has a better qSNR (qSNR = 3.6727) and good performance for fetal ECG extraction in comparison with the other works for average fmSNR in the range of −30 to −15 dB. Also, with considering the SNR value of −24.7 dB before filtering and SNR = 3.1861 dB after filtering; the SNR improvement of 27.8861 dB has been obtained.

A new method in the extract and noise reduction of fetal ECG from maternal ECG by the combination of NLMS algorithm and S-G filter is proposed.

This study attempts to segment the Swiss travel market based on holiday activities. It is based on data of the 2001 travel market in Switzerland. Cluster and discriminant analysis have been employed in order to segment the data and to explain the differences between the clusters. Hereby, five activity‐clusters could be defined, each representing a set of holiday activities most likely to be exercised. The analysis of the five clusters revealed that two demographic profile variables “occupation” and “size of household” did explain the affiliation to a certain cluster. The same could be found for the following travel profile variables: “destination and duration of the trip”, “total number of participants from a household and “type of trip”. Further research will be necessary to find out if the clusters identified really do fulfil the needed criteria for market segments in order to be used by companies in the travel industry.

The widespread adoption of online purchasing has prompted increasing concerns about product safety, and regulators are beginning to hold e-commerce sites accountable for dangerous product defects. For online consumers, understanding the many inherent safety risks among the extensive array of products they browse is a formidable task. The authors attempt to address this problem via a client-side software artifact that warns shoppers about potential product safety hazards at the point of sale.

In this study, the authors built four candidate designs and assessed their effectiveness by means of a large randomized controlled experiment (n = 466). The authors define effectiveness as significant changes in dependent variables associated with health behaviors and technology adoption.

The authors find that all of the designs score high on adoption likelihood, that designs incorporating highlighting and scoring are better at increasing safety knowledge and that simpler designs are better at enhancing safety awareness.

These findings will inform the design of safety information dissemination systems and open new areas of safety awareness enhancement research. More generally, the authors introduce a novel method of testing text visualization variations and their impact on behavioral decisions.

Exploratory learning is regarded as an important ability for developing knowledge from open environments. During the exploration, learners not only need to acquire new information based on their current interests, but also they need to form new perspectives by incorporating new knowledge into their previous knowledge. This paper seeks to address these issues.

To this end, this paper proposes an approach that includes a concept association bank to recommend related concepts in a domain based on the goal of an exploration. By doing so, learners' knowledge can be expanded beyond their current understanding. An experiment was conducted to investigate how the proposed approach facilitated the learners' exploration.

The results indicated that the concept association bank is a useful mechanism to help learners gain new understanding, including providing exploration directions, reducing complexity and cognitive load, facilitating data‐ and goal‐driven exploration strategies, and commenting on new understanding. The implications of these results are discussed.

Current recommendation systems emphasise a data‐driven strategy, which seeks isolated pieces of information, instead of suggesting directions related to their exploration goal. The problem with such an approach is that learners' exploration will be limited by their existing knowledge. Thus, this paper presents an approach to support both data‐ and goal‐driven strategies.