Blog & Column

踏入2026年,本港多項公共收費及罰款均上調,其中公營醫院住院服務、急症室、門診服務(街症)、藥物等收費均有加價,反映在財政壓力下推動「開源」的現實需要。與此同時,香港經濟尚未完全回暖,各行各業都面臨「要節流、又要提效」的挑戰,醫療體系亦不例外。前線人手緊張,加上人口老化帶來的醫療需求持續上升,令醫療服務壓力倍增。在此背景下,政府近年積極推動「智慧醫療」(Smart Health Care),希望透過數碼化、自動化及AI技術提升整體服務效率與準確度。
香煙完稅標籤制度要求在香港供應或銷售的香煙零售封包,必須在進入市場前已附有有效完稅標籤,以支援控煙政策及打擊私煙。這不僅改變稅務與執法環境,也令煙草供應鏈每個環節都要回應是否已貼標及資料是否可驗證這兩個問題。企業一方面需要嚴格符合法規及未來可能加重的罰則與稽查,另一方面仍要在有限人手、場地及系統條件下維持效率,令香煙完稅標籤制度下是否採用智能貼標或自動化成為必須認真評估的課題。
在香港,多數學校已使用圖書管理系統處理日常行政工作,例如學生借還圖書、管理館藏或製作報表等。這類系統的設計重點在於「管理」,幫助學校更有效率地營運圖書館。
在當前經濟低迷、高利率環境與企業謹慎態勢下,本地市場情緒低落,科技創新領域亦難免受波及。與此同時,內地科技公司紛紛進駐香港,新舊勢力交織,正悄然重塑產業格局。
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Hong Kong companies have long relied on manual labour for labelling processes—a system plagued by complexity, errors, and high costs that limits production efficiency and increases management difficulties. In response, more local enterprises are embracing digitalization, and by adopting Million Tech’s robotic labelling system, they are able to immediately reduce manpower, increase labelling speed and accuracy, and lay a solid foundation for long-term competitiveness.
香港經濟環境日益嚴峻,筆者早前出席一個中小企聚會,得悉一項對本地企業經營者或高管的調查,有逾半受訪者(54.6%)認為市場波動或需求放緩,22.7%更直言已進入「收縮期」;而對2026年的展望,45.5%預測將出現「輕微下滑至重大挑戰」,36.4%只期待「溫和好轉」。
香港企業貼標工序長期依賴人手,工序繁瑣、出錯多且成本高昂,令生產效率受限、管理難度增加。愈來愈多本地企業積極數碼化,選用Million Tech智能貼標系統,即時節省人力,提高速度與準確率,為長遠競爭力鋪路。
Library GO is an advanced, Intelligent Reading Solution platform designed for Hong Kong’s educational institutions. It builds upon the foundations of traditional library management systems, offering robust cataloging, circulation, and inventory features. However, Library GO’s core advantage lies in its innovative approach to reading promotion—it transforms school libraries into dynamic hubs for literacy and active engagement, rather than merely serving as a place to store and lend books.
Industries such as food, pharmaceuticals, logistics, and consumer goods in Hong Kong are demanding faster labelling speed, higher accuracy, and greater production transparency. Smart labelling systems are revolutionizing production processes, delivering 2–3 times faster efficiency compared with manual methods, saving up to 70% of manpower, and achieving speeds of 100–150 pieces per minute per system. This not only reduces operating costs but also allows companies to reallocate staff to higher-value tasks, driving digital transformation and enhancing competitiveness.