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China has been going through a “museum boom” paralleling the domestic tourism boom since 2000; such growth changed the cultural landscape; museums became a vital characteristic of some Chinese cities for both residents and tourists. Encouraged by this growth, the more ambitious “All-for-one Museum (全域博物馆)” was proposed. The physical boundary between museums and living spaces is infinite ambiguity, challenging the idea of museums as “heterotopias.” This study aims to explore the musealization of urban spaces in the context of anthropology and museology, scrutinizing the cultural-political intentions and meanings of these developments, and seeks to ignite further investigation into the reconstruction of historical imaginaries for tourists and urban populations across related disciplines.

This paper examines two cases in Chinese metropolises, Beijing and Shanghai, to illustrate this development of musealization, that is, how the cities actively leverage museological values and methods to connect with their past. In the Beijing case, the authors explore how the local government is leading the effort to musealize the city; in the Shanghai case, they will see how tourists, especially dweller-tourists, navigate through a curated past story in the city and connect their own experience, memory and identity with the place.

The all-for-one museum creates a museal layer projected onto the bigger urban space, even though the authenticity of the “past” is challenged by the modernization development of the city. The authors also find out that for some tourists (especially dweller-tourists), an existential sense of authenticity plays a more significant role as they not only seek to sightsee the past of the city but also to take part in its creation.

This paper discusses two kinds of musealization in cosmopolitan cities of Beijing and Shanghai: top-down and bottom-up. It approaches questions about the musealization of urban spaces from the perspectives of anthropology and museology, and discusses musealization in the specific historical context of China’s modernization process.

The techniques for representing and analyzing business processes are referred to as business process modeling. Many business process modeling methods and their associated tools have been used to capture the characteristics of business processes. However, most methods view business processes from different perspectives and have different features and capabilities. Thus, an important research question is how process designers should select appropriate modeling methods for their BPR initiatives. In this paper, we propose a framework for selecting business process modeling methods based on modeling objectives. This framework can serve as the basis for evaluating modeling methods and generating selection procedures. A general selection procedure is also described. We use an expense claim process as an example to illustrate the application of the selection procedure.

To propose a framework with which to study the efficacy of strategic alliances of small firms in knowledge industries, with an emphasis on research design to examine the issues surrounding the phenomena.

A framework is developed that consists of four constructs, namely conditions, roles and contributions, learning, and efficacy. Details of the constructs are explained.

Management consulting industry proves to be a fertile research ground to study strategic alliances with regard to firm size. Through an illustration, it is shown that the proposed framework can be put into practice to investigate relevant research questions.

The framework has limited generalizability to situations where the clients of the knowledge‐intensive service are not clearly defined up front.

Knowledge industries will benefit from developing taxonomy of expertise. Client firms may benefit from encouraging small firm to form strategic alliances.

The contribution is threefold; identification of the interplay of firm size and the practice of alliance formation in knowledge industries as a viable research topic; a framework with which to examine the efficacy of strategic alliances of small firms in knowledge industries; and proposing to expand the knowledge management research beyond intra‐firm learning.

The purpose of this paper is to explore how boundary-spanning demand-side search (BSDSS) fuels radical technological innovations as well as how innovation appropriability moderates this relationship. In particular, based on Teece’s (1986) argument regarding the appropriability of innovation, the authors divide factors to influence innovation appropriability into two types: external institution related and internal capability related.

This study employs a survey methodology. Specifically, the authors collected a sample composed of 150 high-tech manufacturing Chinese firms.

Results show that BSDSS has a positive effect on radical technological innovations. Further, the authors find that dysfunctional competition and political ties negatively moderate the main effect, whereas firms’ legal and IPRs protection capabilities positively moderate the main effect.

One major limitation is that the findings are based on data derived from Chinese firms, which may limit the generalization of the findings.

The findings suggest that firms competing Chinese market, both Chinese and foreign firms, should actively leverage BSDSS to boost radical technological innovations. Chinese firms should pay attention to the negative roles of appropriability hazards originating from external institutional environment. Foreign firms in Chinese market should be cautious on potential dysfunctional competition from local competitors, such as imitation and intelligence property violation, and enhance appropriability through building internal capabilities, such as legal and IPRs capabilities.

The study highlights the crucial roles of BSDSS in radical technological innovations, as well as the moderating roles of innovation appropriability. These results provide new insights into the drivers of radical technological innovations.

Social network theory emphasizes that, to acquire needed resources, new ventures should cultivate industrial connections (intra-industry ties and extra-industry ties). In the meanwhile human capital theory focuses on entrepreneurs' employment experience, especially with respect to its breadth and depth. This study examines ties and experience to determine whether, in combination, they have positive or negative effects on resource acquisition in new ventures.

This study tests research hypotheses using questionnaire survey data with a sample of entrepreneurs in new ventures. Multivariate regression analysis is used to analyze the data.

Combining intra-industry ties and experience breadth or extra-industry ties and experience depth affects resource acquisition positively, whereas combining intra-industry ties and experience depth or extra-industry ties and experience breadth affects resource acquisition negatively.

Conclusions may be constrained by the limited sample size and source. Rather, the impact of the study lies in its identification of the effects of interaction between network ties and entrepreneurs' experience on resource acquisition. Future research can explore the effects of interaction between other dimensions of network ties and a range of entrepreneurs' experience characteristics on resource acquisition.

Entrepreneurs are provided with effective strategies to make use of their ventures' network ties and their personal accumulated experience in the process of obtaining resources.

The findings enrich the entrepreneurship literature by providing a more nuanced understanding of how and when new ventures' industry ties and entrepreneurs' employment experience together influence resource acquisition.

The purpose of this paper is to investigate the effect of pulsed magnetic field (PMF) with different duty cycles on the melt flow and heat transfer behaviors during direct-chill (DC) casting of large-size magnesium alloy billet and find the appropriate range of duty cycle.

A transient two-dimensional mathematical model coupled electromagnetic field, flow field and thermal field, is conducted to study the melt flow and temperature field under PMF and compared with that under the harmonic magnetic field.

The results reveal that melt vibration and fluctuation are generated due to the instantaneous impact of repeated thrust and pull effects of Lorentz force under PMF. The peak of Lorentz force decreases greatly with the increasing duty cycle, but the melt fluctuation region is expanded with higher duty cycle, which accelerates the interior melt velocity and reduces the temperature gradient at the liquid-solid interface. However, PMF with overly high duty cycle has adverse effect on the melt convection and limited influence on the interior melt. A duty cycle of 20% to 50% is a reasonable range.

This paper can provide guiding significance for the setting of duty cycle parameters on DC casting under PMF.

There are few reports on the effect of PMF parameters during DC casting with applying PMF, especially for duty cycle, a parameter unique to PMF. The findings will be helpful for applying the external field of PMF on DC casting.

Community detection of dynamic networks provides more effective information than static network community detection in the real world. The mainstream method for community detection in dynamic networks is evolutionary clustering, which uses temporal smoothness of community structures to connect snapshots of networks in adjacent time intervals. However, the error accumulation issues limit the effectiveness of evolutionary clustering. While the multi-objective evolutionary approach can solve the issue of fixed settings of the two objective function weight parameters in the evolutionary clustering framework, the traditional multi-objective evolutionary approach lacks self-adaptability.

This paper proposes a community detection algorithm that integrates evolutionary clustering and decomposition-based multi-objective optimization methods. In this approach, a benchmark correction procedure is added to the evolutionary clustering framework to prevent the division results from drifting.

Experimental results demonstrate the superior accuracy of this method compared to similar algorithms in both real and synthetic dynamic datasets.

To enhance the clustering results, adaptive variances and crossover probabilities are designed based on the relative change amounts of the subproblems decomposed by MOEA/D (A Multiobjective Optimization Evolutionary Algorithm based on Decomposition) to dynamically adjust the focus of different evolutionary stages.

The purpose of this paper is to reveal the solute segregation behavior in the molten and solidified regions during direct chill (DC) casting of a large-size magnesium alloy slab under no magnetic field (NMF), harmonic magnetic field (HMF), pulsed magnetic field (PMF) and two types of out-of-phase pulsed magnetic field (OPMF).

A 3-D multiphysical coupling mathematical model is used to evaluate the corresponding physical fields. The coupling issue is addressed using the method of separating step and result inheritance.

The results suggest that the solute deficiency tends to occur in the central part, while the solute-enriched area appears near the fillet in the molten and solidified regions. Applying magnetic field could greatly homogenize the solute field in the two-phase region. The variance of relative segregation level in the solidified cross-section under NMF is 38.1%, while it is 21.9%, 18.6%, 16.4% and 12.4% under OPMF2 (the current phase in the upper coil is ahead of the lower coil), HMF, PMF and OPMF1 (the current phase in the upper coil lags behind the lower coil), respectively, indicating that OPMF1 is more effective to reduce the macrosegregation level.

There are few reports on the solute segregation degree in rectangle slab under magnetic field, especially for magnesium alloy slab. This paper can act a reference to make clear the solute transport behavior and help reduce the macrosegregation level during DC casting.

This paper aims to investigate how top management service commitment (TSC) affects two dimensions of new product development (NPD), speed and product innovativeness, and to examine how dysfunctional competition moderates the effects in emerging economies.

Data were collected from 151 high-tech manufacturing firms in China. In one firm, two different top managers were surveyed to reduce the common method variance. The authors used the seemingly unrelated regression approach to test the hypotheses.

First, TSC negatively influences product innovativeness, an effect that dysfunctional competition attenuates. Second, despite not being significantly positive as hypothesized, the direct effect of TSC on NPD speed remains positive when dysfunctional competition is high rather than low. Third, the findings reveal that product innovativeness increases firm performance, but NPD speed shows no similar effect.

First, top managers should pay attention to the synergistic effect between industrial services and product businesses. Second, manufacturing firms in developing countries need to implement servitization when facing unlawful competitive behaviors.

In literature, the effect of industrial services on NPD is unclear. The present study enriches literature by connecting servitization with NPD and by focusing on the importance of top managers to the implementation of servitization. In addition, the authors extend the servitization literature to emerging economies and thereby provide significant insights into this context.

The purpose of this paper is to assess the impacts on production of five fruit crops from 1961 to 2018 of energy use, CO₂ emissions, farming areas and the labor force in China.

This analysis applied the autoregressive distributed lag-bound testing (ARDL) approach, Granger causality method and Johansen co-integration test to predict long-term co-integration and relation between variables. Four machine learning methods are used for prediction of the accuracy of climate effect on fruit production.

The Johansen test findings have shown that the fruit crop growth, energy use, CO₂ emissions, harvested land and labor force have a long-term co-integration relation. The outcome of the long-term use of CO₂ emission and rural population has a negative influence on fruit crops. The energy consumption, harvested area, total fruit yield and agriculture labor force have a positive influence on six fruit crops. The long-run relationships reveal that a 1% increase in rural population and CO₂ will decrease fruit crop production by −0.59 and −1.97. The energy consumption, fruit harvested area, total fruit yield and agriculture labor force will increase fruit crop production by 0.17%, 1.52%, 1.80% and 4.33%, respectively. Furthermore, uni-directional causality is correlated with the growth of fruit crops and energy consumption. Also, the results indicate that the bi-directional causality impact varies from CO₂ emissions to agricultural areas to fruit crops.

This study also fills the literature gap in implementing ARDL for agricultural fruits of China, used machine learning methods to examine the impact of climate change and to explore this important issue.