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This study aims to analyze government hotline text data and generating forecasts could enable the effective detection of public demands and help government departments explore, mitigate and resolve social problems.

In this study, social problems were determined and analyzed by using the time attributes of government hotline data. Social public events with periodicity were quantitatively analyzed via the Prophet model. The Prophet model is decided after running a comparison study with other widely applied time series models. The validation of modeling and forecast was conducted for social events such as travel and educational services, human resources and public health.

The results show that the Prophet algorithm could generate relatively the best performance. Besides, the four types of social events showed obvious trends with periodicities and holidays and have strong interpretable results.

The research could help government departments pay attention to time dependency and periodicity features of the hotline data and be aware of early warnings of social events following periodicity and holidays, enabling them to rationally allocate resources to handle upcoming social events and problems and better promoting the role of the big data structure of government hotline data sets in urban governance innovations.

Advanced big data analysis and machine learning methods are concurrently used to unleash the value of the data generated by government hotline and help devise intelligent applications including automated process management, standard construction and more accurate dispatched orders to build high-quality government service platforms as more widely data-driven methods are in the process.

In this study, based on the influence of the record specifications of texts related to work orders generated by the government hotline, machine learning tools are implemented and compared to optimize classify dispatching tasks by performing exploratory studies on the hotline work order text, including linguistics analysis of text feature processing, new word discovery, text clustering and text classification.

The complexity of the content of the work order is reduced by applying more standardized writing specifications based on combining text grammar numerical features. So, order dispatch success prediction accuracy rate reaches 89.6 per cent after running the LSTM model.

The proposed method can help improve the current dispatching processes run by the government hotline, better guide staff to standardize the writing format of work orders, improve the accuracy of order dispatching and provide innovative support to the current mechanism.

The objective of this study was to analyse the influencing factors of citizens' dissatisfaction with government services during the COVID-19 pandemic to help government departments identify problems in the service process and possible countermeasures.

The authors first used cosine interesting pattern mining (CIPM) to analyse citizens' complaints in different periods of the pandemic. Second, the potential evaluation indices of customer satisfaction were extracted from the hotline business system through a hypothesis analysis and modelled using multiple regression analysis. During the index transformation and standardization process, a machine-learning algorithm of clustering and emotion analysis was adopted. Finally, the authors used the random forest algorithm to evaluate the importance of the indicators and obtain the indicators more important to citizen satisfaction.

The authors found that the complaint topic, appeal time, urgency of citizens' complaints, citizens' emotions, level of detail in the case record, and processing timeliness and efficiency significantly influenced citizens' satisfaction. When the government addresses complaints in a more standardized and efficient manner, citizens are more satisfied.

During the pandemic, government departments should be more patient with citizens, increase the speed of the case circulation and shorten the processing period of appeals. Staff should record appeals in a more standardized manner, highlighting themes and prioritizing urgent cases to appease citizens and relieve their anxiety.

This paper aims to examine the influence of user characteristics on preference for government service delivery channels. Preferences are understood as citizen use of and satisfaction with digital and traditional government contact modalities. User characteristics are represented by three constructs encapsulating the key elements of citizen features and attitudes.

The constructs are tested on data from a survey of 30 cities in China, resulting in 3,000 respondents, which asked questions on respondents’ use of and satisfaction with traditional modes (hotlines and service center channels) and digital modes (e-government and m-government channels) as well as respondents’ sociodemographics, technological capacity and view of government.

The results showed two important findings. First, service channel use was related to the first and second constructs (sociodemographics and technological capacity). Second, service channel satisfaction showed strong evidence of relation to the third construct, view of government.

The results of this study make an empirical contribution to understanding the features of citizens that influence channel choice for public service contacts.

This study contributes to the understanding of channel choice in three areas. First, it is an empirical study using survey data and so adds to a largely case-based and conceptual literature. Second, by looking at the impact of citizen attitudes about government and not just their sociodemographic features. Third, by examining channel choice in the context of a fast-developing country like China.

Purpose: The evidence regarding the effects of the COVID-19 lockdown on domestic violence is mixed. Studies using hotline call services identify an increase on domestic violence, while studies using police reports find a decrease. One limitation is that most of these studies came from diverse regions using different types of data sources. The purpose of this study is to use two separate data sources to study this question in the same region, and to contribute to the discussion for potential mechanisms that explain this mixed evidence.

Methodology: This study estimates the effects of the COVID-19 lockdown on domestic violence in Mexico City. The authors use two separate data sources: hotline calls and official police reports. Our empirically strategy is based on a difference-in-differences methodology and an event-study design.

Findings: As a consequence of the COVID-19 lockdown, hotline calls for psychological domestic violence increase by 17%, while police reports of domestic violence decrease by 22%. To reconcile these discrepancies between hotline calls and police reports, the authors consider several potential mechanisms. The authors find suggestive evidence that the increase in psychological domestic violence is related to financial stress. Further, the results of this study indicate that the reduction in police reports is related to women facing more barriers to report their abusive intimate partners during the lockdown.

Value: These results confirm that the variation observed in the existing literature is related to the type of data being used. The mixed evidence suggests that more women suffer from psychological domestic violence as captured by hotline calls, while women encounter more barriers to report their abusive husbands to the police as captured by the official police reports.

Studies which look at disaster affected people’s use of communications technologies often fail to take into account people’s communication rights in their analyses, particularly their right to freedom of expression. The purpose of this paper is to draw attention to this issue by exploring the link between freedom of expression, community participation and disaster risk reduction in the use of digital feedback channels offered by aid and government agencies in the aftermath of Typhoon Haiyan.

Ethnographic fieldwork was undertaken in the Philippines between 2014 and 2015 in Tacloban City and Sabay Island, both in the Visayas, which have been affected by Typhoon Haiyan. A total of 101 in-depth interviews were conducted with affected people, local and national officials, community leaders, civil society groups, telecommunications companies and humanitarian agencies.

The interviews reveal that majority of disaster-affected Filipinos chose not to engage with formal feedback platforms offered by government and aid agencies out of fear of giving critical feedback to those in authority. They were concerned about the possibility of losing their entitlement to aid, of being reprimanded by government officers, and of the threat to their lives and of their loved ones if they expressed criticism to the government’s recovery efforts. Nonetheless, 15 per cent used backchannels while 10 per cent availed of the formal means to express their views about the recovery.

The paper sought to draw links between people’s lack of engagement with the formal feedback mechanisms offered by government and aid agencies in the wake of Haiyan and the restrictive sociopolitical environment in the Philippines. Further research could be undertaken to examine how freedom of expression plays a role in disaster prevention and mitigation. Research into this area could potentially provide concrete steps to help prevent the occurrence of disasters and mitigate their impacts.

Freedom of expression and its place in disaster risk reduction is rarely explored in disaster studies. The paper addresses this oversight by examining the lack of engagement by communities affected by Haiyan with digital feedback channels provided by aid agencies and government. The findings suggest that despite the provisions for community participation in DRR under the Philippine Disaster Law, people are prevented to express criticism and dissent which puts into question the spirit and purpose of the law.

This paper highlights the voices of some Muslim American women and identifies the processes of gendered racialization in a context of White supremacy. Informed by Rita Dhamoon’s (2011) intersectional “processes of differentiation” and interviews with 20 Muslim American women, we find gendered patterns of racial violence emanating from state and society. According to the interviews, the primary source of the racial violence against women is “society” while men are targeted in a complex configuration of state and society. We argue that this binary is a mirror of the gendered racialization process of maintaining White supremacy in the United States.

At the end of the case discussion, students should be able to:▪ analyse and discuss networks as a form of social capital;▪ identify and discuss alternative growth strategies for an small, medium, micro enterprise (SMME) in the context of prevailing challenges;▪ use the six domains of the entrepreneurship ecosystem to identify and discuss factors that enhance and challenge a business with particular reference to an SMME; and▪ analyse and understand the key dimensions of entrepreneurial behaviour using the case protagonist as an example.

Nhlanhla Dlamini, the managing director of Maneli Pets based in Johannesburg, South Africa had opened an office in Cincinnati in the USA in July 2019 to take over the distribution and marketing of the company’s high-quality protein pet treats. Just over eight months later, the COVID-19 pandemic exploded across the world resulting in unprecedented disruption to people’s lives, world trade and the global economy.Now, in June 2022, Dlamini contemplated the successes and challenges he had experienced since starting Maneli Pets in 2016, not least of which was parting company with US-based Novel Dog LLC, which had previously marketed and distributed the pet treats. He had built an internationally accredited factory from scratch, produced pet products and a brand that was appealing to the competitive international market, and exported to 12 countries around the world. However, Dlamini had also faced the retrenchment of a large number of staff, the breakdown of the relationship with Novel Dog, the difficulties of setting up a distribution business in the USA along with overseeing the South African factory, and in September 2019, his co-founder, Sipha Ndawonde, had left Maneli Pets.Maneli Pets had served Dlamini’s philanthropic purpose of creating jobs and contributing to the growth of the South African economy. Despite the setback of parting ways with Novel Dog, he hoped to continue to create jobs and return to and exceed the staff numbers he had achieved by 2018, regardless of the hard work involved.In his dual position of managing director of Maneli Pets, based in Johannesburg, and sales director of the distribution and marketing arm, Nandi Pets Inc. in Cincinnati, Dlamini had a global view of the companies’ financials that he realised had been missing initially. Would the new structure of Maneli Pets he had created in 2019 in a pre-pandemic world see the company profitable by the end of 2022? What else could he do to take the company to the next level?

MBA, Masters in Management, Postgraduate Diploma in Business, Executive Education short courses.

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CSS 3: Entrepreneurship.

This study aims to help businesses cope with consumers' no-show behaviour from a multistage perspective. It specifically identifies no-show reasons at each stage of appointment services and proposes the corresponding coping strategies.

By focusing on an outpatient appointment service, we interviewed 921 no-show patients to extract no-show reasons, invited 18 hospital managers to propose coping strategies for these reasons using a Delphi method and evaluated the proposed strategies based on EDAS (Evaluation based on Distance from Average Solution).

The results reveal ten reasons for no-show behaviour (i.e. system service quality, overuse, did not know the appointment, self-judgment, forget, waiting time, lateness, uncontrollable problems, time conflict and service coordination), which have nine coping strategy themes (i.e. prepayment, system intelligence, target, subjective norm, system integration, ease of navigation, reminder, confirmation and cancellation). We classify the ten reasons and nine themes into scheduling, waiting and execution stages of an appointment service.

This study provides a package of coping strategies for no-show behaviour to deal with no-show reasons at each appointment service stage. It also extends the research in pre-service management through appointment services.