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This study aims to identify the determinants of transport mode choice and the constraints on shifting freight in New Zealand (NZ) from road to rail and/or coastal shipping, and to quantify the trade-off between factors affecting shippers’ perceptions, to assist in increasing the share of freight moved by non-road transport modes.

A revealed preference survey of 183 freight shippers, including small and medium enterprises and freight agents in NZ, is used to investigate whether freight shippers’ characteristics affect their ranked preference for attributes related to mode choice and modal shift. Additionally, a rank-ordered logistic (ROL) model is estimated using the ranking data.

The results reveal several distinct types of transport mode choice behaviour within the sample and show how the preferences for timeliness, cost, accessibility, damage and loss, customer service, and suitability vary between industry groups and business types. Also, the ROL method allows us to identify heterogeneity in preferences for mode choice and mode shift factors for freight within NZ.

The results imply that NZ shippers ranked transport time as the most significant constraint upon distributing goods by rail, while accessibility and load size were the most significant constraints upon using coastal shipping. The study also identifies how NZ shippers’ modal shift constraints vary according to the firm’s individual or logistical characteristics.

This study informs freight transport policy makers about the needs of NZ shippers by providing quantitative measures of the intensity of preference for the various mode choice factors.

Those involved in freight transport have a better basis for formulating transport policy.

Purpose — Ranking is a natural task for a search engine; a search engine result page is the most common example. This chapter aims at illustrating the motivations and the concepts of rank correlation in a practical way for the researchers active in the different domains of search engines.

Methodology/approach — To this end, this chapter provides a survey according to a topic-oriented basis of the search engine evaluation literature specifically devoted to or based on rank correlation; the chapter explains and illustrates how statistics is the only approach to rank correlation.

Findings/research limitations/implications — The chapter introduces the pros and cons of rank correlation measures through a light-weight formal description and a number of concrete examples to find the measure that better fit a context.

Practical implications — This chapter provides a blueprint for the application of rank correlation within scientific experimentation or item/service recommendation.

Social implications — Rank correlation analyses impact on the success or failure of a search engine in performing the tasks for which it has been designed and hence on the people's daily life activities.

Originality/value of paper — This chapter places rank correlation within a scientific research perspective and in particular connects to and complements documentation on search engine evaluation.

The chapter considers parameter identification, estimation, and model diagnostics in medium scale DSGE models from a frequency domain perspective using the framework developed in Qu and Tkachenko (2012). The analysis uses Smets and Wouters (2007) as an illustrative example, motivated by the fact that it has become a workhorse model in the DSGE literature. For identification, in addition to checking parameter identifiability, we derive the non-identification curve to depict parameter values that yield observational equivalence, revealing which and how many parameters need to be fixed to achieve local identification. For estimation and inference, we contrast estimates obtained using the full spectrum with those using only the business cycle frequencies to find notably different parameter values and impulse response functions. A further comparison between the nonparametrically estimated and model implied spectra suggests that the business cycle based method delivers better estimates of the features that the model is intended to capture. Overall, the results suggest that the frequency domain based approach, in part due to its ability to handle subsets of frequencies, constitutes a flexible framework for studying medium scale DSGE models.

This chapter explores the development and the role of accounting for research quality in Australia’s Excellence in Research for Australia (ERA) assessment exercise. It tracks the progress of performance measurement systems from quantitative to qualitative measurement within the Australian higher education sector since 1970, leading up to the implementation of a formal ERA in 2010, and its subsequent iterations in 2012, 2015, and 2018. Although only a part of the ERA submissions, now certain published research outputs provide the primary evidence for research quality to most ERA panels and are a significant driver of the final rating awarded. Before the authors assess the 2018 exercise, they will examine the ever-changing role of journal publications as a vehicle for academic research output.

No matter the fact that it represents significant tourist contingents, Generation Z (Gen Z) is still insufficiently known regarding the main habits, fears or behaviours in changed circumstances. The main objective of this research is to examine the differences in travel risks perception among clusters of young tourists (Gen Z) after one year of the COVID-19 pandemic. The research was conducted during Serbia's primary tourism season in the first year of the pandemic (from June to October 2020), and just before Serbia's primary tourism season in the second year of the pandemic (May 2021). In 2020, responses of 206 participants were collected, while in 2021 there were 208 participants. Data were gathered from Tourism and Hospitality students at the University of Novi Sad (Serbia) by applying the questionnaire created for the specific purpose of this research. All respondents were representatives of Gen Z, born between 1997 and 2003. The main findings of the research are indicating the impact of the COVID-19 pandemic outbreak on young tourists' travel plans. Results are also indicating that average scores on health and non-health risks dimensions were significantly higher in the year 2020 than in 2021, as well as that all participants were more concerned with non-health risks than with health risks in both years of the pandemic. Gen Z tourists' response to the COVID-19 pandemic was consistent concern about non-health risks, denying health risks and expecting even some financial benefits from the crisis. The research findings are contributing to building a knowledge base for various tourism stakeholders in terms of developing the guidelines for tourism recovery strategies during and after the COVID-19 outbreak.

Timor-Leste is a small, island country situated between South East Asia, Australia, and the Pacific, where it shares a unique mix of climates from all three neighboring regions (Kirono, 2010). The country achieved independence in 2002 having suffered over 400 years of colonialism and foreign occupation, first by the Portuguese and then by the Indonesians (Sandlund et al., 2001). The post-referendum troubles in 1999 left Timor-Leste with seriously damaged infrastructure and relatively little economic activity (Hill, 2001). However, since 1999, the country has made significant steps forward and despite some upheaval in 2006 has significantly developed in terms of infrastructure and economic activity. Nonetheless, Timor-Leste, as a Small Island Developing State (SIDS) also has a number of other vulnerabilities and challenges to contend with including its mountainous region, relative isolation, dependence upon agriculture, and high levels of unemployment. Timor-Leste has a land mass of 14,874km² with a population of approximately 1 million, which is rapidly increasing (Government of Timor-Leste, 2010). The country is dominated by the central Mountain range of Ramelau with as much as 44% of Timor-Leste's land having a slope of more than 40% and over 70% of the country's population dependent upon agriculture for their livelihood (Sandlund et al., 2001).

The purpose of this chapter was to develop a framework for comprehensive business diagnostics, which can be integrated into the management of small and medium-sized businesses.

The chapter proposes a multiloop model of comprehensive business diagnostics, which provides the company with timely and objective information about the dynamics of its key performance indicators. The model allows enterprises of the real sector to optimize the information acquiring process with the help of the express diagnostics indicators and ensure the high quality and efficiency of the obtained information. Testing of the multiloop model at the Pavlovo Posad Shawl Manufactory JSC involved three stages: express diagnostics (ED), general diagnostics (GD), and comprehensive diagnostics (CD).

The results determined the need to move to the comprehensive diagnostics (CD) loop of the model. The approbation of the suggested model at the shawl manufacture, particularly the CD loop, allowed the authors to identify the key factors influencing the company's main economic and financial indicators.

The proposed multiloop model can be used at enterprises with different forms of ownership, including small and medium-sized businesses, both in Russia and abroad.

A multiloop model of comprehensive business diagnostics provides managerial staff with qualitative real-time information that helps them make informed and effective management decisions.

The proposed multiloop model allows businesses to acquire data about the dynamics of key indicators, determine the factors' impacts on key financial and economic indicators, and ensure high efficiency of management decisions with minimal cost.

The visualization of ranking information in global public policy is moving away from traditional “league table” formats and toward dashboards and interactive data displays. This paper explores the rhetoric underpinning the visualization of ranking information in such interactive formats, the purpose of which is to encourage country participation in reporting on the Sustainable Development Goals. The paper unpacks the strategies that the visualization experts adopt in the measurement of global poverty and wellbeing, focusing on a variety of interactive ranking visualizations produced by the OECD, the World Bank, the Gates Foundation and the ‘Our World in Data’ group at the University of Oxford. Building on visual and discourse analysis, the study details how the politically and ethically sensitive nature of global public policy, coupled with the pressures for “decolonizing” development, influence how rankings are visualized. The study makes two contributions to the literature on rankings. First, it details the move away from league table formats toward multivocal interactive layouts that seek to mitigate the competitive and potentially dysfunctional pressures of the display of “winners and losers.” Second, it theorizes ranking visualizations in global public policy as “alignment devices” that entice country buy-in and seek to align actors around common global agendas.