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This paper aims to study the influence of the different parameters of magnetorheological polishing fluids (MRP fluids) on the surface roughness and material removal rate (MRR) of the workpiece surface in the reciprocating magnetorheological polishing (RMRP) process.

A series of single-factor experiments are performed to evaluate the influence of the concentration of magnetic particles, concentration of abrasive particles and size of abrasive particles on surface processing effects by using the RMRP method. Moreover, the yield stress and viscosity of MRP fluids are studied based on the Bingham plastic model by varying the MRP fluids parameters.

A reasonable parameter of MRP fluids is crucial to the surface roughness and MRR of the workpiece surface, and the optimized parameters are obtained by the single-factor experiments of RMRP. The results are when the concentration of carbonyl iron particles is 40 Vol.%, the concentration of CeO₂ is 5 Vol.% and the size of CeO₂ is 2.5 µm in the MRP fluids, the surface roughness of the workpiece remarkably decreases to 28 nm from the initial 332 nm and the MRR of the workpiece increases to 0.118 mg/min.

In this study, the single-factor experiments for the different parameters of MRP fluids are studied to polish K9 glass by using the RMRP device, and the yield stress and viscosity of MRP fluids are investigated by rheological experiments, which provides reference for a reasonable selection of the MRP fluids parameter in RMRP process.

This paper aims to study the effects of the processing parameters in the reciprocating magnetorheological polishing (RMRP) on abrasive particle trajectory by the simulation analysis, which provides a basis for the machining uniformity of the workpiece.

The principle of the RMRP method is discussed, and a series of simulation analysis of the abrasive particle trajectory are performed to evaluate the effects of the workpiece’s rotational speed, the eccentric wheel’s rotational speed, the eccentricity and the frame gap on abrasive particle trajectory by using the RMRP method.

The processing parameters have a significant influence on the abrasive particle trajectory, and then the machining uniformity of the workpiece is affected. Under certain experimental conditions, the height difference of workpiece measuring points varies between 4 and 11 µm, and the height difference of equal radial measuring points is less than 1.5 µm by optimizing processing parameters.

In this study, the optimal processing parameters can be obtained by the simulation analysis of abrasive particle trajectory, which can replace the experimental methods to obtain the reasonable processing parameters for the machining uniformity of the workpiece. It provides references for the selection of processing parameter values in magnetorheological polishing process.

Studies show the benefits of supplier integration, yet negative attitudes toward supplier integration exist that research fails to explain. The purpose of this paper is to investigate managerial attitudes toward supplier integration and how intra-firm processes and culture affect the formation of such attitudes. In particular, the paper aims to examine the differing influences between the USA and China.

Using multi-group structural equation modeling, the authors re-analyzed the data collected by Nahm et al. (2004) and Li et al. (2014) comprised of responses from 224 US and 117 Chinese manufacturing managers.

The study finds that managerial attitudes toward supplier integration depend on the degree to which a collaborative organizational culture and synchronous manufacturing practices exist within a firm. Moreover, in the Chinese context, the influence of a collaborative organizational culture is lower than the influence of synchronous manufacturing practices. The opposite is found in the US context.

The results suggest that overcoming negative attitudes of supplier integration requires more than simply espousing the benefits of supplier integration; looking deeper into an organization’s internal characteristics and situational context is required. In particular, if the country context already emphasizes the collaborative culture, the organization should focus on synchronous manufacturing practices in order to form a positive attitude toward supplier integration.

This paper is the first to examine how managerial attitudes toward supplier integration are formed. The work is novel because the authors suggest that the formation of managerial attitudes toward supplier integration inter-firm management can be affected by intra-firm management in the minds of managers, which are influenced by country contexts.

This note explores the applicability of evaluation criteria to the problem of evaluating the supply chain strategy (SCS) of an organization. A discussion of SCS evaluation is relevant today, as the validity of the dominant approach – proposed two decades ago and based on matching types – has come into question. While evaluation criteria have a long history in other disciplines, they are new to SCS evaluation. To help supply chain (SC) scholars assess the applicability of evaluation criteria to SCS, this note proposes a tentative set of criteria and provides insights derived from the authors’ recent experience. We propose that the use of criteria for the evaluation of SCS may be a useful alternative, or at least a complement, to the dominant approach. These proposed criteria are currently being validated in a project with a company in Uruguay; we invite further empirical validation by third parties.

This study aims to identify the prominent topics, the distribution and association characteristics of topics and the topic evolutionary trends of Documentary Heritage Preservation and Conservation (DHPAC) research in China.

Keywords of relevant papers in China National Knowledge Infrastructure (CNKI) were extracted as the data source in this study. First, frequency and co-occurrence of keywords of the selected papers were obtained by using SATI. Second, co-word network indicators were calculated with the Pajek software. Then, VOSviewer was applied to optimize the visualization of the sub-communities. Finally, a topics evolution map of this research field was implemented by CorTexT.

The research topics of DHPAC research in China were unbalanced but distinct. Topics of DHPAC research in China possessed inconspicuous orientation and consistency. The core topics had less influence on the overall network. A research system had formed with archival conservation and ancient books conservation as the core research directions. Research in this field had formed four continuous evolutionary paths about ancient books conservation, salvage conservation, archival conservation and archives conservation technology science with topics fusion and differentiation coexisting. Attentions on “ancient books conservation”, “paper relics conservation”, “electronic record”, “digitization”, “minority”, “documents in the republic of China” had increased during the past two decades and new hot topics of DHPAC research kept appearing in China.

This study synthesized and analyzed the research results of DHPAC research in China from a more comprehensive perspective and revealed the topic structure and longitudinal evolution process intuitively with co-word analysis and social network analysis, which can assist researchers to improve research systematization, discover new research directions and seek cooperative research path.

Explained pay dispersion theory (Shaw, Gupta, & Delery, 2002) contends that the consequences of pay dispersion depend on two critical contingencies: (1) the presence of legitimate or normatively acceptable dispersion-creating practices, and the (2) identifiability of individual contributions. In this chapter, the first 20 years of empirical evidence and theoretical offshoots of this theory are reviewed. Other recent studies on the outcomes of horizontal and vertical pay dispersion are also evaluated. The review concludes with an evaluative summary of the literature and the identification of several potential fruitful areas for future research.

In this study, the researchers explored the roles played by digital technologies and digital innovation (DI) in Pakistan's Information, Communication and Technology (ICT) companies' firm performance (FP).

The researchers used a quantitative study to gather cross-sectional data from employees working in Pakistan's ICT companies. The authors based this study's findings on 396 valid samples.

The structural equation modeling (SEM) findings underline that digital capability (DC), digital orientation (DO) and digital transformation (DT) have positive and significant effects on DI and FP. Moreover, there is a positive and significant relationship between DI and FP. Finally, DI mediates DC's, DO's and DT's associations with FP.

By committing to embracing new digital technologies and updating existing DCs to become innovation leaders and to improve FP, the findings will help sectors to take advantage of developing digital technologies and the trend toward digitalization. The results are also valuable for policymakers when considering if SMEs should be provided with more money for the digital up-skilling of their employees. Finally, this study's findings enrich the depth of literature about companies' use of digital technologies.

This study's empirical findings confirm the roles played by DC, DO and DT in improving DI and FP in a developing country such as Pakistan.

Partial least squares structural equation modeling (PLS-SEM) has become popular in the information systems (IS) field for modeling structural relationships between latent variables as measured by manifest variables. However, while researchers using PLS-SEM routinely stress the causal-predictive nature of their analyses, the model evaluation assessment relies exclusively on criteria designed to assess the path model's explanatory power. To take full advantage of the purpose of causal prediction in PLS-SEM, it is imperative for researchers to comprehend the efficacy of various quality criteria, such as traditional PLS-SEM criteria, model fit, PLSpredict, cross-validated predictive ability test (CVPAT) and model selection criteria.

A systematic review was conducted to understand empirical studies employing the use of the causal prediction criteria available for PLS-SEM in the database of Industrial Management and Data Systems (IMDS) and Management Information Systems Quarterly (MISQ). Furthermore, this study discusses the details of each of the procedures for the causal prediction criteria available for PLS-SEM, as well as how these criteria should be interpreted. While the focus of the paper is on demystifying the role of causal prediction modeling in PLS-SEM, the overarching aim is to compare the performance of different quality criteria and to select the appropriate causal-predictive model from a cohort of competing models in the IS field.

The study found that the traditional PLS-SEM criteria (goodness of fit (GoF) by Tenenhaus, R2 and Q2) and model fit have difficulty determining the appropriate causal-predictive model. In contrast, PLSpredict, CVPAT and model selection criteria (i.e. Bayesian information criterion (BIC), BIC weight, Geweke–Meese criterion (GM), GM weight, HQ and HQC) were found to outperform the traditional criteria in determining the appropriate causal-predictive model, because these criteria provided both in-sample and out-of-sample predictions in PLS-SEM.

This research substantiates the use of the PLSpredict, CVPAT and the model selection criteria (i.e. BIC, BIC weight, GM, GM weight, HQ and HQC). It provides IS researchers and practitioners with the knowledge they need to properly assess, report on and interpret PLS-SEM results when the goal is only causal prediction, thereby contributing to safeguarding the goal of using PLS-SEM in IS studies.

One of the fundamental objectives of adopting digital supply chain (DSC) is to uplift the performance of an organization. Although a wide variety of literature confirms the impact of DSC on performance, it is hard to explore as to which dimensions of the performance is affected by DSC and how much. This chapter undertakes discussion on the impact of DSC on the various organizational performance indicators. The chapter also denotes some major key performance indicators (KPIs) that organization can track to gauge the impact of DSC on performance. A brief discussion on the challenges related to the development, adoption, and continuation of KPIs is also appeared in the later part of the chapter. The chapter concludes by denoting that the utilization of digital technologies (DTs) such as artificial intelligence (AI), the Internet of Things (IoT), and complex analytics in DSC has prospects for enhancing the operational efficiency, transparency, and agility of a supply chain (SC). Organizations that adopt these DTs have experienced better demand forecasting, reduced time order fulfillment time, and higher levels of consumer satisfaction. Nonetheless, the successful use of DSC requires development and implantation of KPIs regularly.

Sodium alginate (Na-Alg) is a natural polysaccharide with a rich and renewable production that is widely used in the food, pharmaceutical and daily necessities industries, among other fields. The purpose of this study is to obtain a green and degradable shape memory material, calcium alginate (Ca-Alg) film was prepared and the mechanical properties, the shape memory effect of the film were investigated and confirmed.

The Ca-Alg films were prepared by Na-Alg, calcium chloride (CaCl₂) solution, and flow extension method. Dissolve sodium alginate powder, remove bubbles, pour into petri dish, dry at 60°C, add calcium chloride solution cross-linking and finally dry naturally. The effect of CaCl₂ solution concentration on the mechanical properties of the films were investigated and discussed by universal tensile tester. The shape memory behavior and degradation performance of thin films were verified and studied by the fold-deploy shape memory test and soil embedding method, respectively.

The Ca-Alg films exhibited good mechanical and shape memory properties, with a 72.2% shape memory fixity ratio and a 92.3% shape memory recovery ratio, respectively. For a period of 120 days, the film treated with a 6 wt% CaCl₂ solution degraded at a rate of approximately 53%.

Shape memory polymers (SMPs) as intelligent materials are an important research direction for the development of modern high-tech materials. On the other hand, plastic pollution is a major problem today; as a result, preparing green degradable SMPs is essential.

This study synthesized transparent and degradable shape memory Ca-Alg films using Na-Alg and CaCl₂ solution and the flow extension method.